KR102486026B1 - Method and apparatus for parallel entropy encoding/decoding - Google Patents

Abstract

An entropy decoding method according to the present invention comprises the steps of deriving scheduling information from a header of a bitstream received from an encoder, and inverse-binarizing a partial bitstream constituting the received bitstream using the derived scheduling information ( Rearranging in the order of de-binarization, deriving a bin corresponding to the bitstream based on the rearranged partial bitstream, and inverse binarizing the derived bin to obtain a syntax element. Include steps. According to the present invention, image encoding/decoding efficiency can be improved.

Description

Parallel entropy encoding/decoding method and apparatus {METHOD AND APPARATUS FOR PARALLEL ENTROPY ENCODING/DECODING}

The present invention relates to image processing, and more particularly, to an entropy encoding/decoding method and apparatus.

Recently, as broadcasting services with high definition (HD) resolution are expanded not only domestically but also globally, many users are getting used to high-resolution and high-definition images, and many organizations are accelerating the development of next-generation video equipment. In addition, as interest in UHD (Ultra High Definition) having a resolution four times higher than that of HDTV increases along with HDTV, a compression technology for a higher resolution and higher quality image is required.

For image compression, inter prediction technology predicts pixel values included in the current picture from temporally previous and/or subsequent pictures, and predicts pixel values included in the current picture using pixel information in the current picture. An intra prediction technique, an entropy coding technique in which short codes are assigned to symbols with a high frequency of occurrence and long codes are assigned to symbols with a low frequency of occurrence may be used.

A technical problem of the present invention is to provide an image encoding method and apparatus capable of improving image encoding/decoding efficiency.

Another technical problem of the present invention is to provide an image decoding method and apparatus capable of improving image encoding/decoding efficiency.

Another technical problem of the present invention is to provide an entropy encoding method and apparatus capable of improving image encoding/decoding efficiency.

Another technical problem of the present invention is to provide an entropy decoding method and apparatus capable of improving image encoding/decoding efficiency.

1. An embodiment of the present invention is an entropy decoding method. The method comprises deriving scheduling information from a header of a bitstream received from an encoder, de-binarizing a partial bitstream constituting the received bitstream using the derived scheduling information Rearranging in order, deriving a bin corresponding to the bitstream based on the rearranged partial bitstream, and inversely binarizing the derived bin to obtain a syntax element. wherein the scheduling information includes information about positions of each of the partial bitstreams constituting the received bitstream and information about an inverse binarization order of the partial bitstreams.

2. In 1, the entire probability interval for the LPB (Least Probable Bin) probability of the bin is classified into a plurality of probability intervals each having a representative probability, and the partial bitstream is composed of at least one codeword, Codewords constituting the partial bitstream may correspond to the same representative probability.

3. The step of deriving the bin comprises deriving codeword length information from a header of the received bitstream and deriving a bin corresponding to the bitstream based on the derived codeword length information. It may further include, and the codeword length information may be information about a minimum length and a maximum length of a codeword for a representative probability of each of the plurality of probability intervals.

4. The step of deriving the bins includes determining a codeword-bin mapping table for representative probabilities of each of the plurality of probability intervals using the derived codeword length information, and the determined codeword - The method may further include deriving a bin corresponding to the bitstream by using a bin mapping table.

5. Another embodiment of the present invention is an entropy decoding device. The apparatus derives scheduling information from a header of a bitstream received from an encoder, and uses the derived scheduling information to de-binarize a partial bitstream constituting the received bitstream in order of de-binarization. A bitstream determiner that rearranges according to the rearranged partial bitstream, a bin decoder that derives bins corresponding to the bitstream based on the rearranged partial bitstream, and a syntax element by inversely binarizing the derived bins ( syntax element), and the scheduling information includes information about the position of each of the partial bitstreams constituting the received bitstream and an inverse binarization order of the partial bitstream contains information about

6. In 5, the entire probability interval for the LPB (Least Probable Bin) probability of the bin is classified into a plurality of probability intervals each having a representative probability, and the partial bitstream is composed of at least one codeword, Codewords constituting the partial bitstream may correspond to the same representative probability.

7. The method of 6, further comprising a codeword length calculator for deriving codeword length information from a header of the received bitstream, wherein the bin decoder corresponds to the bitstream based on the derived codeword length information A bin may be derived, and the codeword length information may be information about a minimum length and a maximum length of a codeword with respect to a representative probability of each of the plurality of probability intervals.

8. The method of 7 may further include a mapping table determiner for determining a codeword-bin mapping table for a representative probability of each of the plurality of probability intervals using the derived codeword length information, wherein the bin The decoder may derive a bin corresponding to the bitstream using the determined codeword-bin mapping table.

9. Another embodiment of the present invention is a video decoding method. The method comprises deriving scheduling information from a header of a bitstream received from an encoder, de-binarizing a partial bitstream constituting the received bitstream using the derived scheduling information Rearranging in order, deriving a bin corresponding to the bitstream based on the rearranged partial bitstream, and inversely binarizing the derived bin to obtain a syntax element. and generating a reconstructed image using the obtained syntax element, wherein the scheduling information includes information about a position of each of the partial bitstreams constituting the received bitstream and an inverse binarization order of the partial bitstream contains information about

10. In 9, the entire probability interval for the LPB (Least Probable Bin) probability of the bin is classified into a plurality of probability intervals each having a representative probability, and the partial bitstream is composed of at least one codeword, Codewords constituting the partial bitstream may correspond to the same representative probability.

11. The step of deriving the bin comprises deriving codeword length information from a header of the received bitstream and deriving a bin corresponding to the bitstream based on the derived codeword length information. It may further include, and the codeword length information may be information about a minimum length and a maximum length of a codeword for a representative probability of each of the plurality of probability intervals.

12. The method of 11, wherein the deriving the bin comprises determining a codeword-bin mapping table for a representative probability of each of the plurality of probability intervals using the derived codeword length information, and the determined codeword - The method may further include deriving a bin corresponding to the bitstream by using a bin mapping table.

According to the video encoding method according to the present invention, video encoding/decoding efficiency can be improved.

According to the video decoding method according to the present invention, video encoding/decoding efficiency can be improved.

According to the entropy encoding method according to the present invention, image encoding/decoding efficiency can be improved.

According to the entropy decoding method according to the present invention, image encoding/decoding efficiency can be improved.

1 is a block diagram showing a configuration according to an embodiment of an image encoding apparatus to which the present invention is applied.
2 is a block diagram showing a configuration according to an embodiment of a video decoding apparatus to which the present invention is applied.
3 is a table schematically illustrating one embodiment of codeword length restrictions according to the present invention.
4 is a conceptual diagram schematically illustrating an embodiment of a scheduling method for a bitstream parsing process according to the present invention.
5 is a conceptual diagram schematically illustrating another embodiment of a scheduling method for a bitstream parsing process according to the present invention.
6 is a block diagram schematically illustrating an embodiment of a parallel entropy encoding apparatus according to the present invention.
7 is a block diagram schematically illustrating an embodiment of a parallel entropy decoding apparatus according to the present invention.
8 is a block diagram schematically illustrating another embodiment of a parallel entropy encoding apparatus according to the present invention.
9 is a block diagram schematically illustrating another embodiment of a parallel entropy decoding apparatus according to the present invention.
10 is a block diagram schematically illustrating another embodiment of a parallel entropy encoding apparatus according to the present invention.
11 is a schematic block diagram of another embodiment of a parallel entropy decoding apparatus according to the present invention.
12 is a flowchart schematically illustrating an embodiment of a parallel entropy encoding method according to the present invention.
13 is a flowchart schematically illustrating an embodiment of a parallel entropy decoding method according to the present invention.

EMBODIMENT OF THE INVENTION Hereinafter, embodiment of this invention is described concretely with reference to drawings. In describing the embodiments of the present specification, if it is determined that a detailed description of a related known configuration or function may obscure the gist of the present specification, the detailed description thereof will be omitted.

It is understood that when a component is referred to as “connected” or “connected” to another component, it may be directly connected or connected to the other component, but other components may exist in the middle. It should be. In addition, the description of "including" a specific configuration in the present invention does not exclude configurations other than the corresponding configuration, and means that additional configurations may be included in the practice of the present invention or the scope of the technical spirit of the present invention.

Terms such as first and second may be used to describe various components, but the components should not be limited by the terms. These terms are only used for the purpose of distinguishing one component from another. For example, a first element may be termed a second element, and similarly, a second element may be termed a first element, without departing from the scope of the present invention.

In addition, components appearing in the embodiments of the present invention are shown independently to represent different characteristic functions, and do not mean that each component is made of separate hardware or a single software component unit. That is, each component is listed and included as each component for convenience of explanation, and at least two components of each component can be combined to form a single component, or one component can be divided into a plurality of components to perform a function, and each of these components can be divided into a plurality of components. Integrated embodiments and separated embodiments of components are also included in the scope of the present invention as long as they do not depart from the essence of the present invention.

In addition, some of the components may be optional components for improving performance rather than essential components that perform essential functions in the present invention. The present invention can be implemented by including only components essential to implement the essence of the present invention, excluding components used for performance improvement, and a structure including only essential components excluding optional components used for performance improvement. Also included in the scope of the present invention.

1 is a block diagram showing a configuration according to an embodiment of an image encoding apparatus to which the present invention is applied.

Referring to FIG. 1 , the video encoding apparatus 100 includes a motion estimation unit 111, a motion compensation unit 112, an intra prediction unit 120, a switch 115, a subtractor 125, and a transform unit 130. , a quantization unit 140, an entropy encoding unit 150, an inverse quantization unit 160, an inverse transform unit 170, an adder 175, a filter unit 180, and a reference picture buffer 190.

The image encoding apparatus 100 may encode an input image in an intra mode or an inter mode and output a bitstream. In the case of the intra mode, the switch 115 may be switched to the intra mode, and in the case of the inter mode, the switch 115 may be switched to the inter mode. After generating a prediction block for an input block of an input image, the image encoding apparatus 100 may encode a residual between the input block and the prediction block.

In the case of the intra mode, the intra prediction unit 120 may generate a prediction block by performing spatial prediction using pixel values of previously encoded blocks adjacent to the current block.

In the case of the inter mode, the motion estimation unit 111 may obtain a motion vector by finding a region that best matches the input block in the reference picture stored in the reference picture buffer 190 during the motion prediction process. The motion compensator 112 may generate a prediction block by performing motion compensation using a motion vector.

The subtractor 125 may generate a residual block by a difference between the input block and the generated prediction block. The transform unit 130 may output a transform coefficient by performing transform on the residual block. The quantization unit 140 may quantize the input transform coefficient according to a quantization parameter and output a quantized coefficient.

The entropy encoding unit 150 may output a bit stream by performing entropy encoding based on the values calculated by the quantization unit 140 or the encoding parameter values calculated in the encoding process.

When entropy encoding is applied, a small number of bits are allocated to a symbol with a high probability of occurrence and a large number of bits are allocated to a symbol with a low probability of occurrence to represent the symbol, thereby reducing the number of bits for symbols to be coded. The size of the column may be reduced. Therefore, compression performance of image encoding can be improved through entropy encoding. The entropy encoding unit 150 may use an encoding method such as exponential golomb, context-adaptive variable length coding (CAVLC), or context-adaptive binary arithmetic coding (CABAC) for entropy encoding.

Since the video encoding apparatus according to the embodiment of FIG. 1 performs inter-prediction encoding, that is, inter-prediction encoding, a currently encoded video needs to be decoded and stored in order to be used as a reference video. Therefore, the quantized coefficient is inversely quantized in the inverse quantization unit 160 and inversely transformed in the inverse transformation unit 170. The inverse quantized and inverse transformed coefficients are added to the prediction block through an adder 175, and a reconstructed block is generated.

The reconstructed block passes through a filter unit 180, and the filter unit 180 applies at least one of a deblocking filter, a sample adaptive offset (SAO), and an adaptive loop filter (ALF) to the reconstructed block or the reconstructed picture. can do. The filter unit 180 may also be called an adaptive in-loop filter. The deblocking filter may remove block distortion generated at a boundary between blocks. SAO may add an appropriate offset value to a pixel value to compensate for a coding error. ALF may perform filtering based on a value obtained by comparing a reconstructed image with an original image. A reconstructed block that has passed through the filter unit 180 may be stored in the reference picture buffer 190 .

2 is a block diagram showing a configuration according to an embodiment of a video decoding apparatus to which the present invention is applied.

* Referring to FIG. 2, the video decoding apparatus 200 includes an entropy decoding unit 210, an inverse quantization unit 220, an inverse transform unit 230, an intra prediction unit 240, a motion compensation unit 250, an adder 255, a filter unit 260, and a reference picture buffer 270.

The image decoding apparatus 200 may receive the bitstream output from the encoder, perform decoding in an intra mode or inter mode, and output a reconstructed image, that is, a reconstructed image. In the intra mode, the switch may be converted to intra, and in the case of the inter mode, the switch may be converted to inter. The video decoding apparatus 200 may generate a reconstructed block, that is, a reconstructed block, by obtaining a reconstructed residual block from the input bitstream, generating a prediction block, and then adding the reconstructed residual block and the prediction block. .

The entropy decoding unit 210 may generate symbols including symbols in the form of quantized coefficients by entropy decoding the input bitstream according to a probability distribution. The entropy decoding method is similar to the entropy encoding method described above.

When the entropy decoding method is applied, a small number of bits are allocated to a symbol with a high probability of occurrence and a large number of bits are allocated to a symbol with a low probability of occurrence to express the symbol, thereby increasing the size of the bit stream for each symbol. can be reduced Therefore, compression performance of image decoding may be improved through the entropy decoding method.

The quantized coefficients are inversely quantized in the inverse quantization unit 220 and inversely transformed in the inverse transform unit 230, and as a result of inverse quantization/inverse transformation of the quantized coefficients, a reconstructed residual block may be generated.

In the case of the intra mode, the intra prediction unit 240 may generate a prediction block by performing spatial prediction using pixel values of previously encoded blocks adjacent to the current block. In the case of the inter mode, the motion compensation unit 250 may generate a prediction block by performing motion compensation using a motion vector and a reference image stored in the reference picture buffer 270 .

The reconstructed residual block and the prediction block are added through the adder 255, and the added block may pass through the filter unit 260. The filter unit 260 may apply at least one of a deblocking filter, SAO, and ALF to a reconstructed block or a reconstructed picture. The filter unit 260 may output a reconstructed image, that is, a restored image. The reconstructed image may be stored in the reference picture buffer 270 and used for inter prediction.

As described above with reference to FIGS. 1 and 2 , the encoder and the decoder may respectively perform entropy encoding and entropy decoding. When entropy encoding/decoding is applied, a small number of bits are allocated to a symbol with a high probability of occurrence and a large number of bits are allocated to a symbol with a low probability of occurrence to represent the symbol. size may be reduced. Methods used for entropy encoding/decoding may include exponential Gollum, CAVLC, CABAC, and the like.

For example, a table for performing entropy encoding/decoding, such as a variable length coding (VLC) table, may be stored in the encoder and decoder, and the encoder and decoder perform entropy encoding/decoding using the stored variable length encoding table. can be done

The encoder and decoder may derive a binarization method of the target symbol and a probability model of the target symbol/bin, and then perform entropy encoding/decoding using the derived binarization method or probability model. there is.

Here, binarization means representing the value of a symbol as a binary sequence/string. A bin means a value (0 or 1) of each binary number when a symbol is expressed as a sequence of binary numbers through binarization. A probability model means a predicted probability of a symbol/bin to be encoded/decoded that can be derived through context information/context model. The context information/context model refers to information for determining a probability of a symbol/bin to be coded/decoded.

More specifically, the CABAC entropy encoding method converts non-binarized symbols into bins by binarization, and constructs a context model using encoding information of surrounding and encoding target blocks or information of symbols/bins encoded in a previous step. A bit stream may be generated by determining a bin occurrence probability and predicting a bin occurrence probability according to the determined context model and performing arithmetic encoding of the bin.

That is, the encoder/decoder can effectively perform entropy encoding/decoding by using the encoding/decoding information of neighboring blocks and the probability of occurrence of bins encoded/decoded in the previous step. Also, in the encoding step, the encoder may select a context model through encoding information of neighboring blocks, and update information about the occurrence probability of bins generated according to the selected context model.

When a single encoder and/or a single decoder is used for a UHD-level image having a size equal to or greater than HD-level, a workload required for a single processor is very large and image processing speed may be very slow. Accordingly, a method of improving encoding efficiency through parallelization of encoding and/or decoding processes may be provided. To this end, a parallelization method for processes such as motion compensation, image interpolation, discrete cosine transform (DCT), and quantization may be provided, and the parallelization method may also be applied to the above-described entropy encoding/decoding process.

Parallel entropy encoding/decoding may be performed using a plurality of entropy encoders and/or a plurality of entropy decoders. A technique used for parallel entropy encoding/decoding includes Probability Interval Partitioning Entropy (PIPE), which maps and/or converts a variable-length bin sequence into a variable-length codeword. ) and variable length to variable length (V2V). The PIPE and V2V schemes can be applied to both single entropy coder/decoder and parallel entropy coder/decoder.

In the process of parallel entropy encoding/decoding, the probability of a bin may be divided according to a quantization interval. Each of the divided probability intervals may be allocated to a bin encoder corresponding to each probability interval at the encoder side, and may be allocated to a bin decoder corresponding to each probability interval at the decoder side. In addition, a representative probability value corresponding to each probability interval may exist in each divided probability interval. When PIPE or V2V technology is used for parallel entropy encoding/decoding, a plurality of entropy encoders/decoders are assigned to each Least Probable Bin (LPB) probability interval and a representative LPB probability value corresponding to the probability interval Encoding using / Decryption can be performed. Here, LPB may mean a bin value that appears less among bin values of 0 and 1. Hereinafter, in embodiments to be described later, a probability interval may mean an LPB probability interval, and a representative probability may mean a representative LPB probability.

In the encoder, each parallelized entropy coder codes bins with a fixed representative probability, and the encoder may transmit a set of output codewords to the decoder in the form of a bitstream. For example, the encoder may binarize symbols to be encoded and convert them into bins, and predict and/or derive LPB probability values for each bin to be encoded through a context modeler and/or a probability predictor. The encoder may derive a probability interval for each bin and a representative LPB probability for each probability interval using the LPB probability value predicted through the context modeler and/or the probability predictor. Each bin may be entropy-coded in a bin encoder to which a probability interval corresponding to the bin is assigned. In this case, a bin sequence input to each bin encoder may be converted into a codeword by a codeword table. That is, bin sequences input to each bin encoder can be output in the form of codewords through codeword table mapping. The output codeword may be included in a bitstream and transmitted to a decoder in Network Abstraction Layer (NAL) units.

The bitstream transmitted to the decoder may be parsed by the decoder. In the parsing process, the decoder may map and/or convert a codeword of variable length into an empty sequence of variable length. In this case, overhead may occur in a comparison process for each bin.

In addition, the number of entropy decoders included in the encoder may be different from the number of entropy decoders included in the decoder. For example, when an encoded bitstream is transmitted to the decoder and decoded, the number of entropy decoders is It may be smaller than the number of encoders. In this case, for example, each entropy decoder may parse a bitstream corresponding to one representative probability and then parse a bitstream corresponding to another representative probability. After parsing, each bin is decoded into a value of a meaningful syntax element through a de-binarization process, so the above-described parsing process may cause a delay in the de-binarization step, which reduces the overall entropy It can have a big impact on the decoding speed.

In order to reduce the delay in the debinarization step, each entropy encoder included in the encoder may add information about a decodable position in the bitstream to a header of the bitstream, and the information about the decodable position may be added to the header. The bitstream included in may be transmitted to the decoder. In the present specification, the decodable position may mean a point where entropy decoding starts and/or a point where entropy decoding ends in a minimum unit bitstream. In addition, the minimum unit bitstream may represent a minimum unit in which entropy decoding is performed within a bitstream transmitted from an encoder to a decoder, and for example, the minimum unit bitstream corresponds to one codeword. It can be. In this case, each entropy decoder may perform entropy decoding from an intermediate point of the bitstream (eg, a starting point of the minimum unit bitstream) instead of a starting point of the entire bitstream. The decoder may perform scheduling for a bitstream parsing process in each entropy decoder using information about a decodable position included in a header of a bitstream. However, even when the information on the decodable position is used as described above, since a bin before debinarization is performed after parsing cannot be recognized as a value of a meaningful syntax element, a delay occurs in the debinarization step. and the output of the entropy decoder may be delayed.

As described above, when a delay occurs in the parsing process and the debinarization process, the parallel entropy encoding/decoding speed may decrease. Therefore, a parallel entropy encoding/decoding method capable of minimizing the delay occurring in the parsing process and debinarization process is required.

3 is a table schematically illustrating one embodiment of codeword length restrictions according to the present invention. 3 shows the minimum and maximum lengths of codewords for each fixed probability value of an LPB that can be a representative LPB probability.

When a codeword that is an output of the entropy encoder is generated, the length of the codeword may have a variable value. However, as described above, when a codeword of variable length is converted and/or mapped into an empty sequence of variable length in a decoder, a large amount of computation is required, and thus overhead may occur in the codeword parsing process. Accordingly, a codeword of a predetermined fixed length may be used, and in this case, the parsing speed of the decoder may be improved. However, when a codeword of a predetermined fixed length is used, a problem that encoding efficiency is reduced may occur.

Accordingly, in order to reduce overhead occurring in the parsing process, the length of the codeword may be limited to a minimum length or a maximum length. The minimum length and the maximum length of the codeword may be defined for each representative LPB probability of the parallel entropy encoder. That is, the minimum length and the maximum length of the codeword may be defined in consideration of representative LPB probability values of each entropy encoder in the encoder.

For example, an encoder may include a codeword length calculator. The codeword length calculator may derive an optimal codeword length (minimum length and maximum length) for each fixed probability value that may be a representative probability in consideration of encoding efficiency. In this case, each entropy encoder included in the encoder may generate a codeword having a length greater than or equal to the minimum length and less than or equal to the maximum length according to a representative probability value corresponding thereto. Figure 3 shows an embodiment of the minimum length and maximum length of the derived codeword.

Referring to FIG. 3, for each fixed probability value, a maximum length and a minimum length of a codeword may be derived. For example, when the fixed probability value is 0.5, the maximum length of the codeword may be 8 and the minimum length of the codeword may be 6. Also, when the fixed probability value is 0.005, the maximum length of the codeword may be 13 and the minimum length of the codeword may be 1.

Also, in the embodiment of FIG. 3 , the higher the fixed probability value, the smaller the maximum length value of the codeword and the larger the minimum length value. Therefore, the larger the fixed probability value of the LPB, the smaller the variance of the codeword length value, and the smaller the fixed probability value of the LPB, the larger the variance of the codeword length value.

The minimum length and maximum length of the codeword derived for each fixed probability value are not limited to the above-described embodiment, and may be derived in various forms depending on circumstances. Hereinafter, information on the minimum length and maximum length of a codeword derived from an encoder is referred to as codeword length information.

Codeword length information derived from the encoder may be included in a header of the bitstream and transmitted to the decoder. In this case, the decoder may map or convert the codeword into an empty sequence using the transmitted codeword length information, and the parallel entropy decoding speed may be improved.

4 is a conceptual diagram schematically illustrating an embodiment of a scheduling method for a bitstream parsing process according to the present invention.

4 illustrates a scheduling method when the number of bin encoders included in the encoder and the number of bin decoders included in the decoder are the same. In the embodiment of FIG. 4 , it is assumed that the number of empty encoders and the number of empty decoders are 4, respectively.

410 of FIG. 4 represents an embodiment of a bitstream output from an encoder and transmitted to a decoder. Each block constituting the bitstream (blocks separated by a dotted line) may represent a minimum unit bitstream, and for example, each minimum unit bitstream may correspond to one codeword. A number indicated in each minimum unit bitstream may indicate an order in which inverse binarization is performed after parsing. In addition, each of 411, 413, 415, and 417 of FIG. 4 may indicate a set of all minimum unit bitstreams corresponding to a representative probability of one bin coder. Hereinafter, a set of all minimum unit bitstreams corresponding to one representative probability and/or one probability interval is referred to as a representative probability unit bitstream.

420 of FIG. 4 illustrates an embodiment of a method for allocating the bitstream of FIG. 410 to cores of a four bin decoder. Referring to 420 of FIG. 4 , one representative probability unit bitstream may be allocated to a core of one bin decoder. Here, the core may mean a processor that performs calculations. In this case, each bin decoder may perform entropy decoding on the representative probability unit bitstream allocated thereto.

After parsing, each bin can be decoded into a meaningful syntax element value through a debinarization process. In this case, a parsing process in which the bitstream is converted into an empty sequence may be performed independently of the debinarization process. For example, an order in which a bitstream is converted into an empty sequence and an order in which inverse binarization is performed may be separately determined. Therefore, in 420 of FIG. 4 , parsing of bins required in the debinarization step is delayed, and thus the debinarization process may be delayed. That is, the parsing process according to the embodiment of 420 of FIG. 4 may cause a delay in the debinarization step, which may cause a delay in the entire entropy decoder. Accordingly, an entropy decoding method capable of reducing a delay generated in an inverse binarization process may be provided.

430 of FIG. 4 shows another embodiment of a bitstream output from an encoder and transmitted to a decoder. Each block constituting the bitstream (blocks separated by a dotted line) may represent a minimum unit bitstream, and for example, each minimum unit bitstream may correspond to one codeword. A number indicated in each minimum unit bitstream may indicate an order in which inverse binarization is performed after parsing. In addition, each of 433, 435, 437, and 439 of FIG. 4 may represent a representative probability unit bitstream.

In addition, the bitstream header 431 of 430 of FIG. 4 may include scheduling information for scheduling a bitstream parsing process. Here, scheduling may refer to a process of rearranging a bitstream by considering an inverse binarization order of syntax elements of symbols. When scheduling is performed, the rearranged bitstream may be allocated to an empty decoder. A specific embodiment of the scheduling information will be described later.

440 of FIG. 4 illustrates an embodiment of a method for allocating the bitstream of FIG. 430 to the cores of a four bin decoder.

Referring to 440 of FIG. 4 , one representative probability unit bitstream may be classified and/or divided into a plurality of partial bitstreams. Here, the partial bitstream may represent an entropy decoding unit determined by an encoder for rearrangement of the bitstream, and one partial bitstream may include one or a plurality of minimum unit bitstreams. When the representative probability unit bitstream is divided into partial bitstreams, each entropy decoder is performed at the middle point of the bitstream (eg, the starting point of the partial bitstream) instead of the starting point of the entire representative probability unit bitstream. You can start parsing.

The decoder may determine a bitstream allocated to each bin decoder by rearranging the partial bitstream so that the bins that are preferentially needed in the debinarization process are parsed first, considering the debinarization order of the syntax elements of the symbol. At this time, the decoder may allocate the bitstream in consideration of the number of empty decoders so that the plurality of empty decoders can have a similar amount of work.

A point at which the representative probability unit bitstream is divided and/or classified into partial bitstreams may be determined in an encoder, and a parsing priority for each representative probability unit bitstream and/or each partial bitstream may also be determined in the encoder. there is. In the determination process, the encoder may determine the partial bitstream and priority by considering the inverse binarization order of the syntax elements of the symbol.

Hereinafter, in this specification, information about points at which a representative probability unit bitstream is divided and/or classified into partial bitstreams is referred to as partial bitstream information, and for each representative probability unit bitstream and/or each partial bitstream Information about the priority of parsing is referred to as priority information. The above-described scheduling information may include the partial bitstream information and the priority information, and may include additional information necessary for scheduling when there is additional information.

If the scheduling information is determined, the entropy encoder may add the determined scheduling information to the header 431 of the bitstream and transmit it to the decoder. The decoder may recognize a representative probability unit bitstream having a high priority and/or a partial bitstream having a high priority based on the transmitted scheduling information, and may perform parsing in units of the partial bitstream. The decoder can perform scheduling of the bitstream parsing process based on the scheduling information to minimize delay occurring in the debinarization step.

According to the above-described method, work can be smoothly distributed among a plurality of empty decoders included in the decoder, and delay in the debinarization step can be minimized. Accordingly, an output delay of the parallel entropy decoder can be minimized, and an entropy decoding process can be speeded up.

5 is a conceptual diagram schematically illustrating another embodiment of a scheduling method for a bitstream parsing process according to the present invention.

5 illustrates a scheduling method when the number of bin decoders included in the decoder is smaller than the number of bin coders included in the encoder. In the embodiment of FIG. 5 , it is assumed that the number of bin coders is 4 and the number of bin decoders is 3.

510 of FIG. 5 represents an embodiment of a bitstream output from an encoder and transmitted to a decoder. Each block constituting the bitstream (blocks separated by a dotted line) may represent a minimum unit bitstream, and for example, each minimum unit bitstream may correspond to one codeword. A number indicated in each minimum unit bitstream may indicate an order in which inverse binarization is performed after parsing. In addition, each of 511, 513, 515, and 517 of FIG. 5 may represent a representative probability unit bitstream. In 510 of FIG. 5 , a total of four representative probability unit bitstreams may exist.

520 of FIG. 5 illustrates an embodiment of a method for allocating the bitstream of FIG. 510 to the cores of three bin decoders. Referring to 520 of FIG. 5 , one representative probability unit bitstream may be allocated to a core of one bin decoder. In this case, each bin decoder may perform entropy decoding on the representative probability unit bitstream allocated thereto.

In 520 of FIG. 5 , since the number of bin decoders is three, when parsing starts, one representative probability unit bitstream may be allocated to each of the three bin decoders. In this case, the representative probability unit bitstream not allocated to the bin decoder may be parsed after at least one of the three representative probability unit bitstreams allocated to the bin decoder is all parsed. In this case, a bin with a higher debinarization priority is parsed later than a bin with a lower debinarization priority, and thus a delay may occur in the debinarization process. That is, the parsing process according to the embodiment of 520 of FIG. 5 may cause a delay in the debinarization step, which may cause a delay in the entire entropy decoder. Accordingly, an entropy decoding method capable of reducing a delay generated in an inverse binarization process may be provided.

530 of FIG. 5 represents another embodiment of a bitstream output from an encoder and transmitted to a decoder. Each block constituting the bitstream (blocks separated by a dotted line) may represent a minimum unit bitstream, and for example, each minimum unit bitstream may correspond to one codeword. A number indicated in each minimum unit bitstream may indicate an order in which inverse binarization is performed after parsing. In addition, each of 533, 535, 537, and 539 of FIG. 5 may represent a representative probability unit bitstream.

Also, the bitstream header 531 of 530 of FIG. 5 may include scheduling information for scheduling a bitstream parsing process. Here, the scheduling information may include partial bitstream information and priority information, and may include additional information necessary for scheduling if it exists. When scheduling is performed, the reordered bitstream may be allocated to three empty decoders.

540 of FIG. 5 illustrates an embodiment of a method for allocating the bitstream of FIG. 530 to the cores of a three bin decoder.

Referring to 540 of FIG. 5 , one representative probability unit bitstream may be classified and/or divided into a plurality of partial bitstreams. Here, one partial bitstream may include one or a plurality of minimum unit bitstreams. When the representative probability unit bitstream is divided into partial bitstreams, each entropy decoder is performed at the middle point of the bitstream (eg, the starting point of the partial bitstream) instead of the starting point of the entire representative probability unit bitstream. You can start parsing.

The decoder may determine a bitstream allocated to each bin decoder by rearranging the partial bitstream so that the bins that are preferentially needed in the debinarization process are parsed first, considering the debinarization order of the syntax elements of the symbol. At this time, the decoder may allocate the bitstream in consideration of the number of empty decoders so that the plurality of empty decoders can have a similar amount of work.

Scheduling information (partial bitstream information and priority information) necessary to perform the above-described scheduling process may be determined by an encoder. In the determination process, the encoder may determine the partial bitstream and priority by considering the inverse binarization order of the syntax elements of the symbol. When the scheduling information is determined, the entropy encoder may add the determined scheduling information to the header 531 of the bitstream and transmit it to the decoder.

The decoder may recognize a representative probability unit bitstream having a high priority and/or a partial bitstream having a high priority based on the transmitted scheduling information, and may perform parsing in units of the partial bitstream. The decoder can perform scheduling of the bitstream parsing process based on the scheduling information to minimize delay occurring in the debinarization step.

According to the above-described method, work can be smoothly distributed among a plurality of empty decoders included in the decoder, and delay in the debinarization step can be minimized. Accordingly, an output delay of the parallel entropy decoder can be minimized, and an entropy decoding process can be speeded up.

6 is a block diagram schematically illustrating an embodiment of a parallel entropy encoding apparatus according to the present invention.

The parallel entropy encoding apparatus according to the embodiment of FIG. 6 includes a binarizer 610, a probability estimator 620, a probability quantizer 630, a codeword length calculator 640, It may include a mapping table calculator 650, a bin sequence calculator 660, a bin encoder 670, a buffer 680, and a bitstream determiner 690. The parallel entropy encoding apparatus according to the embodiment of FIG. 6 may include a plurality of bin encoders 670 to perform parallel entropy encoding.

Referring to FIG. 6 , the binarizer 610 may binarize each syntax element obtained in the encoding step. At this time, each syntax element may be converted into an empty sequence by the binarization process. Here, the empty sequence may be composed of a combination of 0 and 1. The probability predictor 620 may predict the LPB probability for each of the bins obtained by the binarization process.

The stochastic quantizer 630 may perform LPB stochastic quantization on each of the bins by dividing the stochastic interval in order to increase coding efficiency. That is, the probability quantizer 630 can determine which probability interval each bin corresponds to by using the LPB probability of the predicted bin. The stochastic quantizer 630 may determine a bin coder 670 used for entropy encoding among a plurality of bin coders according to a probability interval corresponding to each bin for each bin.

The codeword length calculator 640 may derive and/or obtain an optimal codeword length (minimum length and maximum length) for each representative probability value in consideration of encoding efficiency. At this time, the codeword length calculator 640 may determine the minimum length and the maximum length of the codeword based on the characteristics of the representative probability value in order to maintain encoding efficiency.

As an embodiment, information on the minimum and maximum lengths of the derived codeword (codeword length information) may be included in a header of a bitstream and transmitted to a decoder. In this case, the decoder may determine the minimum length and the maximum length of the codeword parsed by each bin decoder using the codeword length information included in the header.

In another embodiment, the maximum length and minimum length of the codeword for each representative probability may be derived using the same algorithm in the encoder and decoder. In this case, the maximum length and minimum length of the codeword may be derived based on the representative probability value of each bin coder.

According to the above-described embodiment, since the codeword length is limited to a certain range by the codeword length calculator 640, the bitstream parsing speed can be improved.

The mapping table calculator 650 may select and/or generate a mapping table using codeword length information generated by the codeword length calculator 640 . Here, the mapping table may be used in a process of converting and/or mapping empty sequences into codewords. Accordingly, the mapping table may be referred to as a codeword-bin mapping table.

As an example, the minimum length and maximum length of a codeword may be predetermined fixed values. In this case, predetermined mapping tables for each codeword length value within the range may be equally stored in the encoder and decoder. When the minimum and maximum lengths of codewords are the same, one fixed-length mapping table may be stored.

The encoder may select and use one of the stored mapping tables. In addition, the encoder may add mapping table selection information indicating which mapping table is used among the stored mapping tables to a header of the bitstream and transmit the same to the decoder. At this time, the decoder may select one mapping table from among a plurality of stored mapping tables using the transmitted mapping table selection information.

As another example, the mapping table may be generated using the same generation algorithm in an encoder and a decoder. At this time, the encoder and decoder may generate a mapping table corresponding to each codeword length within a codeword length range determined by the minimum length and the maximum length.

In addition to the generation algorithm, if additional information for generating a mapping table exists, the encoder may add the additional information to a header of the bitstream and transmit the additional information to the decoder. Here, the additional information may include, for example, information about the maximum length and minimum length of the codeword. At this time, the decoder may generate a mapping table using information on the maximum length and minimum length of the transmitted codeword.

In the above case, the encoder may select and use one of the generated mapping tables. Also, the encoder may add mapping table selection information indicating which mapping table is used among the generated mapping tables to a header of the bitstream and transmit the same to the decoder. In this case, the decoder may select one mapping table from among a plurality of mapping tables using the transmitted mapping table selection information.

The bin sequence calculator 660 can derive information about the binarization/inverse binarization order of syntax elements of symbols and information about the probability of each bin. The bin sequence calculator 660 may derive scheduling information for a bitstream parsing process based on the derived information. Here, scheduling may refer to a process of rearranging a bitstream by considering an inverse binarization order of syntax elements of symbols.

As described above with reference to FIG. 4 , scheduling information may include partial bitstream information and priority information, and may include additional information necessary for scheduling if it exists. Here, the partial bitstream information indicates information about a point at which a representative probability unit bitstream is divided into partial bitstreams, and the priority information is a parsing priority for each representative probability bitstream and/or each partial bitstream. information about can be displayed.

As described above, the number of bin coders included in the encoder may be different from the number of bin decoders included in the decoder, and for example, the number of bin decoders may be smaller than the number of bin decoders. In this case, a bin with a higher debinarization priority is parsed later than a bin with a lower debinarization priority, and thus a delay may occur in the debinarization process. At this time, the scheduling information derived from the bin sequence calculator 660 is used in the entropy decoding process, so that the delay generated in the inverse binarization process can be minimized. In order to add and/or include the derived scheduling information in the header of the bitstream, the bin sequence calculator 660 may send the scheduling information to the bitstream determiner 690.

When the information derived from the above-described codeword length calculator 640 and bin sequence calculator 660 is used for entropy decoding, output delay of the parallel entropy decoder can be minimized. Accordingly, the entropy decoding process can be speeded up.

The bin encoder 670 may perform entropy encoding on each bin using the mapping table derived by the mapping table calculator 650. Each bin encoder 670 may convert binarized bins into codewords using a mapping table corresponding to a representative probability. Codewords output from the bin encoder 670 may be stored in the buffer 680.

The codewords stored in the buffer may be transmitted or stored to a decoder through the bitstream determiner 690. The bitstream determiner 690 may add header information to the header of the bitstream. The header information may include, for example, codeword length information, mapping table selection information, information added to generate a mapping table, scheduling information, and the like. The bitstream determiner 690 may transmit the generated bitstream to a decoder. The decoder can minimize decoding delay and improve output speed by limiting the codeword length or rearranging the bitstream using header information included in the transmitted bitstream.

7 is a block diagram schematically illustrating an embodiment of a parallel entropy decoding apparatus according to the present invention.

The parallel entropy decoding apparatus according to the embodiment of FIG. 7 includes a codeword length calculator 710, a mapping table calculator 720, a bitstream determiner 730, a bin decoder 740, a buffer 750, a probability quantizer ( 760), a probability predictor 770 and an inverse binarizer 780. The parallel entropy decoding apparatus according to the embodiment of FIG. 7 may include a plurality of bin decoders 740 to perform parallel entropy decoding.

Referring to FIG. 7 , a codeword length calculator 710 may derive codeword length information from a header of a bitstream transmitted from an encoder.

As described above, due to the variable length of the codeword, overhead may be generated in the bitstream parsing process, and the parsing speed may be reduced. In order to solve this problem, in the encoder, the minimum length and the maximum length of the codeword may be determined for each of the representative LPB probabilities of the parallel entropy encoder.

As an embodiment, information on the minimum and maximum lengths of the derived codeword (codeword length information) may be included in a header of a bitstream and transmitted to a decoder. In this case, the decoder may determine the minimum length and the maximum length of the codeword parsed by each bin decoder using the codeword length information included in the header.

In another embodiment, the maximum length and minimum length of the codeword for each representative probability may be derived using the same algorithm in the encoder and decoder. In this case, the maximum length and minimum length of the codeword may be derived based on the representative probability value of each bin coder.

According to the above-described embodiment, since the codeword length is limited to a certain range by the codeword length calculator 710, the bitstream parsing speed can be improved.

The mapping table calculator 720 may select and/or generate a mapping table using codeword length information derived by the codeword length calculator 710 . In this case, the mapping table may be selected and/or generated based on the representative probability of each bin decoder 740 .

As an example, the minimum length and maximum length of a codeword may be predetermined fixed values. In this case, predetermined mapping tables for each codeword length value within the range may be equally stored in the encoder and decoder. When the minimum and maximum lengths of codewords are the same, one fixed-length mapping table may be stored.

The encoder may select and use one of the stored mapping tables. In addition, the encoder may add mapping table selection information indicating which mapping table is used among the stored mapping tables to a header of the bitstream and transmit the same to the decoder. At this time, the decoder may select one mapping table from among a plurality of stored mapping tables using the transmitted mapping table selection information.

As another example, the mapping table may be generated using the same generation algorithm in an encoder and a decoder. At this time, the encoder and decoder may generate a mapping table corresponding to each codeword length within a codeword length range determined by the minimum length and the maximum length.

In addition to the generation algorithm, if additional information for generating a mapping table exists, the encoder may add the additional information to a header of the bitstream and transmit the additional information to the decoder. Here, the additional information may include, for example, information on the maximum length and minimum length of the codeword, and the maximum length and minimum length of the codeword may be determined for each of the representative LPB probabilities of the parallel entropy encoder. . At this time, the decoder may generate a mapping table using information on the maximum length and minimum length of the transmitted codeword.

In the above case, the encoder may select and use one of the generated mapping tables. Also, the encoder may add mapping table selection information indicating which mapping table is used among the generated mapping tables to a header of the bitstream and transmit the same to the decoder. In this case, the decoder may select one mapping table from among a plurality of mapping tables using the transmitted mapping table selection information.

In the above-described embodiment, the mapping table is determined using codeword length information transmitted from the encoder. Therefore, the length of the codeword for each representative probability can be limited, the delay of the parsing process can be minimized, and the output speed of the bin decoder 740 can be improved.

The bitstream determiner 730 may decode header information included in the header of the bitstream transmitted from the encoder. The header information may include, for example, scheduling information (partial bitstream information and/or priority information). The bitstream determiner 730 may classify each representative probability unit bitstream into a partial bitstream using the scheduling information, and may perform scheduling on a bitstream input to the bin decoder 740 . In this case, the decoder may allocate the bitstream to the bin decoders in consideration of the number of bin decoders so that the plurality of bin decoders may have similar workloads. Since specific embodiments of the scheduling method have been described above with reference to FIGS. 4 and 5, it will be omitted.

The bitstream determiner 730 can minimize input delay in the debinarization step by performing scheduling on the bitstream using the scheduling information transmitted from the encoder.

When the information derived from the above-described codeword length calculator 710 and bitstream determiner 730 is used for entropy decoding, the output speed of the parallel entropy decoder can be improved. Accordingly, the entropy decoding process can be speeded up.

Each bin decoder 740 may convert a codeword into a bin sequence using a mapping table corresponding to a scheduled bitstream and a representative probability. At this time, the bitstream input to each bin decoder 740 may be determined according to the representative LPB probability, for example.

The bins output from the bin decoder 740 may be input to the probability predictor 770 through the buffer 750 and the probability quantizer 760 in order. The probability predictor 770 may derive an LPB probability for an input bin. After passing through the probability predictor 770, the empty sequence may be decoded into a value of a meaningful syntax element through an inverse binarizer 780.

8 is a block diagram schematically illustrating another embodiment of a parallel entropy encoding apparatus according to the present invention.

The parallel entropy encoding apparatus according to the embodiment of FIG. 8 includes a binarizer 810, a probability predictor 820, a probability quantizer 830, a codeword length calculator 840, a mapping table calculator 850, and a bin An encoder 860 and a buffer 870 may be included. The parallel entropy encoding apparatus according to the embodiment of FIG. 8 may include a plurality of bin encoders 860 to perform parallel entropy encoding.

As described above, the encoder may limit the length of the codeword in order to improve output speed of the decoder by reducing overhead generated in the parsing process. Since encoding efficiency may be reduced when a codeword having a predetermined fixed length is used, the encoder may determine a minimum length and a maximum length of the codeword for each bin encoder and/or bin decoder.

Referring to FIG. 8 , the codeword length calculator 840 may derive and/or obtain an optimal codeword length (minimum length and maximum length) for each representative probability value of an empty encoder in consideration of encoding efficiency. there is. At this time, the codeword length calculator 840 may determine the minimum length and the maximum length of the codeword based on the characteristics of the representative probability in order to maintain encoding efficiency.

In the embodiment of FIG. 8 , operations of other components except for the above-described components are the same as in the embodiment of FIG. 6 and thus are omitted.

9 is a block diagram schematically illustrating another embodiment of a parallel entropy decoding apparatus according to the present invention.

The entropy decoding apparatus according to the embodiment of FIG. 9 includes a codeword length calculator 910, a mapping table calculator 920, a bin decoder 930, a buffer 940, a probability quantizer 950, and a probability predictor. (960) and inverse binarizer (970). The parallel entropy decoding apparatus according to the embodiment of FIG. 9 may include a plurality of bin decoders 930 to perform parallel entropy decoding. The parallel entropy decoding apparatus according to the embodiment of FIG. 9 may operate similarly to the parallel entropy decoding apparatus according to the embodiment of FIG. 7 .

A bitstream transmitted from the encoder may be allocated to a plurality of bin decoders 930 included in the decoder. In this case, the decoder may determine a bitstream allocated to each bin decoder using header information included in a header of the transmitted bitstream. In this case, due to the variable length of the codeword, overhead may be generated in the process of parsing the bitstream, and the parsing speed may be reduced. To solve this problem, the codeword length calculator 910 may determine a minimum length and a maximum length of a codeword for each of the representative LPB probabilities of the parallel entropy encoder.

As an embodiment, information about the minimum and maximum lengths of codewords derived from the encoder (codeword length information) may be included in a header of a bitstream and transmitted to a decoder. At this time, the codeword length calculator 910 may determine the minimum and maximum lengths of codewords parsed by each bin decoder using the codeword length information included in the header.

In another embodiment, the maximum length and minimum length of the codeword for each representative probability may be derived using the same algorithm in the encoder and decoder. In this case, the maximum length and minimum length of the codeword may be derived based on the representative probability value of each bin coder.

The mapping table calculator 920 uses information about the representative probability of each bin decoder 930 and information about the minimum and maximum lengths of the codeword determined by the codeword length calculator 910 , the mapping table can be determined. Since the specific embodiment of the method of determining the mapping table has been described in detail with reference to FIG. 7 , it will be omitted.

The output speed of the parallel entropy decoder can be improved by the codeword length calculator 910 and the mapping table calculator 920 described above. Accordingly, the entropy decoding process can be speeded up.

In the embodiment of FIG. 9 , operations of other components except for the above-described components are the same as in the embodiment of FIG. 7 and thus are omitted.

* FIG. 10 is a block diagram schematically illustrating another embodiment of a parallel entropy encoding apparatus according to the present invention.

The parallel entropy encoding apparatus according to the embodiment of FIG. 10 includes a binarizer 1010, a probability predictor 1020, a probability quantizer 1030, a bin sequence calculator 1040, a bin encoder 1050, a buffer ( 1060) and a bitstream determiner 1070. The parallel entropy encoding apparatus according to the embodiment of FIG. 10 may include a plurality of bin encoders 1050 to perform parallel entropy encoding.

Referring to FIG. 10 , each syntax element obtained in the encoding step of the binarizer 1010 may be binarized. At this time, each syntax element may be converted into an empty sequence by the binarization process. The probability predictor 1020 may calculate an occurrence probability for each of the bins obtained through the binarization process. Also, the probability quantizer 1030 may perform LPB probability quantization for each bin by dividing the probability interval.

The bin sequence calculator 1040 may derive scheduling information for a bitstream parsing process. As described above with reference to FIG. 4 , scheduling information may include partial bitstream information and priority information, and may include additional information necessary for scheduling if it exists. Here, the partial bitstream information indicates information about a point at which a representative probability unit bitstream is divided into partial bitstreams, and the priority information is a parsing priority for each representative probability bitstream and/or each partial bitstream. information about can be displayed.

As described above, in the parsing process, bins with a high debinarization priority may be parsed later than bins with a low debinarization priority, and in this case, a delay may occur in the debinarization process. At this time, the scheduling information derived from the bin sequence calculator 1040 is used in the entropy decoding process, so that the delay generated in the inverse binarization process can be minimized. In order to add and/or include the derived scheduling information in the header of the bitstream, the bin sequence calculator 1040 may send the scheduling information to the bitstream determiner 1070. The bitstream determiner 1070 may add the scheduling information to a header of a bitstream, and the bitstream may be transmitted to a decoder.

The output speed of the parallel entropy decoder can be improved by the bin sequence calculator 1040 described above. Accordingly, the entropy decoding process can be speeded up.

In the embodiment of FIG. 10 , operations of other components except for the above-described components are the same as those in the embodiment of FIG. 6 and thus are omitted.

11 is a schematic block diagram of another embodiment of a parallel entropy decoding apparatus according to the present invention.

The entropy decoding apparatus according to the embodiment of FIG. 11 includes a bitstream determiner 1110, a bin decoder 1120, a buffer 1130, a probability quantizer 1140, a probability predictor 1150, and an inverse binarizer ( 1160). The parallel entropy decoding apparatus according to the embodiment of FIG. 11 may include a plurality of bin decoders 930 to perform parallel entropy decoding. The parallel entropy decoding apparatus according to the embodiment of FIG. 11 may operate similarly to the parallel entropy decoding apparatus according to the embodiment of FIG. 7 .

The bitstream determiner 1110 may decode header information included in the header of the bitstream transmitted from the encoder. The header information may include, for example, scheduling information (partial bitstream information, priority information, and/or additional information required for bitstream rearrangement). The bitstream determiner 1110 may classify each representative probability unit bitstream into a partial bitstream using the scheduling information, and perform scheduling on a bitstream input to the bin decoder 1120. In this case, the decoder may determine a bitstream allocated to each bin decoder in consideration of the number of bin decoders so that the plurality of bin decoders may have a similar amount of work.

The bitstream determiner 1110 can minimize input delay in the debinarization step by performing scheduling on the bitstream using the scheduling information transmitted from the encoder.

*

* In the embodiment of FIG. 11, operations of the other components except for the above-described components are the same as those in the embodiment of FIG. 7, so they are omitted.

12 is a flowchart schematically illustrating an embodiment of a parallel entropy encoding method according to the present invention.

Referring to FIG. 12, the encoder may convert syntax elements into an empty sequence using a predetermined binarization method (S1210). Here, the bin sequence may be composed of a combination of 0 and 1, and each 0 or 1 may be referred to as a bin.

The encoder may determine LPB probabilities for each of the binarized bins (S1220), and divide probability intervals of bins according to quantization intervals (S1230).

Also, the encoder may derive scheduling information in order to minimize an input delay in the decoder's inverse binarization step (S1240). As described above, the scheduling information may include partial bitstream information and priority information, and if there is additional information necessary for scheduling, it may also include the additional information. The derived scheduling information may be included in a header of a bitstream and transmitted to a decoder.

As described above, probability intervals of bins may be divided according to quantization intervals, and each divided probability interval may be allocated to a bin coder corresponding to each probability interval. The encoder may determine a bin coder used for entropy encoding of each bin through quantization according to a probability interval corresponding to each bin (S1250).

The encoder may derive codeword length information for each representative LPB probability of an empty encoder by a predetermined algorithm (S1260). Here, the codeword length information may be, for example, information about a minimum length and a maximum length of a codeword. When codeword length information is derived, the encoder may determine a mapping table using the derived codeword length information. Here, the mapping table may refer to a table used in a process of converting and/or mapping empty sequences into codewords.

The encoder may perform bin encoding on each bin using the determined mapping table (S1270). The encoder may convert binarized bins into codewords by performing bin encoding. The output codeword may be included in a bitstream and transmitted to a decoder in NAL units.

13 is a flowchart schematically illustrating an embodiment of a parallel entropy decoding method according to the present invention.

Referring to FIG. 13, the decoder may receive a bitstream from the encoder (S1310). The header of the received bitstream may include header information. Here, the header information may include, for example, codeword length information, mapping table selection information, information added to create a mapping table, scheduling information, and the like.

The decoder may derive scheduling information from the header of the bitstream, and may perform scheduling on the bitstream using the derived scheduling information to minimize input delay in the debinarization step (S1320). Here, scheduling may refer to a process of rearranging a bitstream by considering an inverse binarization order of syntax elements of symbols. In this case, the decoder may allocate the bitstream to the bin decoders in consideration of the number of bin decoders so that the plurality of bin decoders may have similar workloads.

Referring back to FIG. 13, the decoder may derive codeword length information from the header of the bitstream transmitted from the encoder (S1330). Here, the codeword length information may mean information on the minimum and maximum lengths of codewords corresponding to representative LPB probabilities of each bin decoder. When codeword length information is derived, the decoder may determine a mapping table using the derived codeword length information.

The decoder may perform bin decoding on each bin using the determined mapping table (S1340). At this time, the plurality of bin decoders included in the decoder may decode bins corresponding to probability intervals allocated thereto. The decoder may convert the codeword into bins by performing bin decoding.

After going through a probability quantization step, the decoder may determine an LPB probability for each bin output from the bin decoder (S1350). Also, the decoder may derive a value of a meaningful syntax element by performing inverse binarization on each bin output from the bin decoder (S1360).

In the foregoing embodiments, the methods are described on the basis of a flowchart as a series of steps or blocks, but the present invention is not limited to the order of steps, and some steps may occur in a different order or concurrently with other steps as described above. can In addition, those skilled in the art will understand that the steps shown in the flow chart are not exclusive, that other steps may be included, or that one or more steps of the flow chart may be deleted without affecting the scope of the present invention. You will understand.

The foregoing embodiment includes examples of various aspects. It is not possible to describe all possible combinations to represent the various aspects, but those skilled in the art will recognize that other combinations are possible. Accordingly, it is intended that the present invention cover all other substitutions, modifications and variations falling within the scope of the following claims.

Claims (3)

decoding partial bitstream information about a splitting point of a plurality of partial bitstreams from the bitstream;
obtaining encoding order information indicating an encoding order of the plurality of partial bitstreams;
decoding the plurality of partial bitstreams according to the encoding order information; and
Reconstructing an image based on the decoded partial bitstream;
The bitstream is divided into a header area and a data area,
The header area includes the partial bitstream information,
The data area of the bitstream includes the plurality of partial bitstreams, and an end point of each of the plurality of partial bitstreams is determined based on partial bitstream information of each of the plurality of partial bitstreams;
For decoding of the current partial bitstream, between an end point of the previous partial bitstream determined from partial bitstream information of the previous partial bitstream and an end point of the current partial bitstream determined from partial bitstream information of the current partial bitstream The bit string of is parsed,
By parsing the bit string, quantized transform coefficients are generated,
By inverse quantizing and inverse transforming the quantized transform coefficient, a residual block is generated,
The image decoding method characterized in that the image is reconstructed according to the residual block.
encoding an image to obtain syntax elements;
determining partial bitstream information about a splitting point of a plurality of partial bitstreams;
Determining encoding order information indicating an encoding order of the plurality of partial bitstreams; and
Encoding the syntax element, the partial bitstream information, and the encoding order information to generate a bitstream;
The bitstream is divided into a header area and a data area,
The header area includes the partial bitstream information,
In the data area of the bitstream, partial bitstream information of each of the plurality of partial bitstreams is used to determine an end point of each of the plurality of partial bitstreams;
the partial bitstream information of the current partial bitstream indicates a bit stream of the current partial bitstream according to an end point of a previous partial bitstream and an end point of the current partial bitstream;
To generate the bit string, a residual block for a predetermined block of an image is generated,
The image encoding method characterized in that the image is encoded according to the transformation and quantization of the residual block.
A computer-readable recording medium storing a bitstream received by an image decoding apparatus and used to restore a current block included in an image,
The bitstream includes syntax elements, partial bitstream information, and encoding order information;
The bitstream is divided into a header area and a data area,
The header area includes the partial bitstream information,
The data area of the bitstream includes a plurality of partial bitstreams;
Characterized in that the partial bitstream information of each of the plurality of partial bitstreams is used to determine an end point of each of the plurality of partial bitstreams in the bitstream,
Characterized in that the encoding order information indicates an encoding order for the plurality of partial bitstreams,
the partial bitstream information of the current partial bitstream indicates a bit stream of the current partial bitstream according to an end point of a previous partial bitstream and an end point of the current partial bitstream;
To generate the bit string, a residual block for a predetermined block of an image is generated,
A computer-readable recording medium storing a bitstream, characterized in that the image is encoded according to the transformation and quantization of the residual block.

Images