CN102595132A - Distributed video encoding and decoding method applied to wireless sensor network - Google Patents
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Abstract
一种应用于无线传感器网络的分布式视频编解码方法，采用基于感兴趣区域提取的视频编解码框架，鉴于残差视频编解码的优点，结合二者融合应用的优点，突破了单独采用残差视频编解码的局限性。残差编码可以去除视频序列的时间冗余度，但是对于运动激烈的区域，进行残差编码反而会使系统性能变差。本发明利用基于感兴趣区域提取框架的分布式视频编解码体系的特点：区分出运动激烈区域和非激烈区域。对其中的非激烈区域块进行残差块编解码，可以使系统获得更优的率失真特性，最终达到降低传感器节点的能耗目的。
A distributed video encoding and decoding method applied to wireless sensor networks, using a video encoding and decoding framework based on region of interest extraction, in view of the advantages of residual video encoding and decoding, combined with the advantages of the fusion of the two, it breaks through the single use of residual Limitations of video codecs. Residual coding can remove the temporal redundancy of video sequences, but for areas with intense motion, residual coding will make the system performance worse. The present invention utilizes the characteristics of the distributed video codec system based on the region-of-interest extraction framework: to distinguish intense motion regions and non-intense regions. Coding and decoding the residual blocks in the non-intense area blocks can make the system obtain better rate-distortion characteristics, and finally achieve the purpose of reducing the energy consumption of sensor nodes.
Description
Technical field
The present invention relates to a kind of distributed video decoding method that is applied to wireless sensor network, specifically is a kind of video coding-decoding method based on area-of-interest extraction and prediction residual encoding and decoding, belongs to the wireless multimedia sensor network field.
Background technology
In recent years, be accompanied by the wireless multimedia communication technology rapid development, some new Video Applications demands begin to occur, as: wireless pc video camera, mobile video telephone, wireless video monitoring, wireless multimedia sensor network etc.In these new Video Applications, owing to be subject to electric quantity of power supply, memory capacity, computing capability, communication capacity, wireless video terminal not only needs the coding of lower complexity, and needs vision signal real-time coding and transmission.Traditional video encoding standard (like MPEG, H.26X) has all adopted hybrid encoding frame; Coding adopts estimation; Fully excavate the time and the spatial coherence information of video sequence, generally speaking, encoder complexity is 5～10 times of decoding complex degree; No longer be applicable in these new Video Applications occasions, must seek new code compression method.A kind of brand-new coding and decoding video framework-distributed video coding (Distributed VideoCoding; DVC) be subjected to scholar's extensive concern; This video coding has been broken through the constraint of conventional video coding, adopts intraframe coding and interframe decoding technique, carries out interframe prediction decoding through the correlation of excavating vision signal in decoding end; Thereby removed the complicated inter prediction of coding side; Have the characteristic of low complicated coding, and have good coding robustness characteristics, can satisfy these new Video Applications demands preferably.The distributed video encoding and decoding have a wide range of applications as a core technology in all fields.
Relatively more classical at present distributed coding and decoding scheme mainly comprises the Wyner-Ziv video coding that Girod of Stanford University and Aaron etc. propose; The PRISM video coding that the Ramchandran of University of California Berkeley etc. propose; The layering Wyner-Ziv video coding that Zixiang Xiong proposes; The state-free distributed video coding that Sehgal etc. propose is based on the distributed video coding of wavelet coding and various visual angles distributed video coding etc.Traditional based on turbo or LDPC to the indiscriminate coding of the All Ranges of Wyner-Ziv frame; The encoding process of this mode; For the more violent zone of motion and the fringe region of motion object, motion estimation techniques can not accurately predict, need be to the more feedback information of coding side request during decoding; So not only increased code check, and the parts of images of decoding is still accurate inadequately.
In the Wyner-Ziv video coding, the motion estimation techniques of decoding end is to carry out motion-vector prediction according to the correlation of interframe to realize.When the correlation between decoding end side information and the Wyner-Ziv frame is more weak, just can accurately not carry out estimation, and then the effect of influence decoding.Be about to the violent and motion target edges zone of motion based on area-of-interest exacting method, extract, adopt the entropy coding mode, thereby improve the efficient of coding side and the quality of decoded picture as ROI.
Aaron and Girod etc. carry out residual prediction at coding side to the W frame, again prediction residual are carried out the LDPC coding; In decoding end, can generate better side information through estimation, to be used for the reconstruct decoded frame.Utilize the relativity of time domain of video sequence to encode,, improved distortion performance though increased the storage of coding side frame and the amount of calculation that interframe is subtracted each other.
Summary of the invention
Technical problem: according to the above-mentioned said advantage of extracting the distributed video coding of encoding based on area-of-interest with prediction residual; The invention provides and a kind of the prediction residual coding thinking is applied to the distributed decoding method in the area-of-interest extraction scheme; It is a kind of distributed video decoding method that is applied to wireless sensor network; Its adopts through combining the two advantage of area-of-interest exacting method and prediction residual coding method, has further obtained better distortion performance.
Technical scheme: the specific algorithm framework that extracts based on area-of-interest: video flowing to be encoded is divided into key frame (K) and Wyner-Ziv frame (WZ); The K frame adopts the conventional coding scheme; The WZ frame extracts according to area-of-interest and distinguishes algorithm; Adopt the ROI judgment criterion that macro block is divided into ROI macro block and non-ROI macro block, the ROI macro block is taked entropy encoding/decoding, non-ROI macro block is taked the mode of LDPC encoding and decoding.
The thought of prediction residual coding is applied in the middle of the encoding and decoding of non-ROI macro block.The macro block X of current ROI macro block X and last key frame same position
ErSubtract each other residual block X-X
Er, the generation residual block is carried out the LDPC coding.Decoding end makes X through the side information piece Y of estimation interpolation generation X
ErCopy to decoding end, get residual error side information piece Y-X
ErUtilize this residual information piece decoded residual piece X-X
Er, when rebuilding non-ROI macro block, add reference block X at last
Er
One, architecture
The main body of the architecture of the used distributed video coding of the present invention is based on transform domain Wyner-Ziv video coding system, comprises that in addition area-of-interest extracts part and residual error encoding and decoding part.
Two, method flow
The concrete steps that are applied to the distributed video decoding method of wireless sensor network are:
Step 1. marks off the K frame and the W frame of video sequence,
Step 2. pair K frame carries out encoding and decoding in the frame,
ROI (the Region Of Interest) macro block that step 3. selects a kind of area-of-interest extraction algorithm to distinguish in the W frame is the area-of-interest of image, refers to the more violent zone of motion in the image, with non-ROI macro block, is designated as X simultaneously;
Step 4. pair ROI macro block adopts entropy encoding/decoding; (common entropy coding has: LZW coding, Shannon (Shannon) coding, Huffman (Huffman) coding and arithmetic coding (arithmetic coding).Entropy coding is a kind of harmless coded system.)
Step 5. pair non-ROI macro block takes the residual error encoding and decoding promptly the residual error of image to be carried out encoding and decoding;
Step 6. is recovered video sequence according to the K frame and the W frame that decode, accomplishes distributed encoding and decoding.
In above step 4, the ROI macro block is adopted entropy encoding/decoding, be that the prediction residual coding thinking is applied in the encoding and decoding of area-of-interest piece, concrete steps are:
Same position macro block work difference X-X in non-ROI macro block and the key frame in the step 41. calculating W frame
Er, obtain residual image;
Step 42. pair this residual image carries out the LDPC coding;
Step 43. is through carrying out the side information Y that estimation obtains the LDPC decoding to K frame and the W frame that reconstructs; Side information Y deducts reference block X
ErBe the macro block that is positioned at same position in the key frame with non-ROI macro block, thereby obtain difference side information Y-X
Er
Step 44. reconstructs residual block X '-X according to this difference side information
Er
Step 45. is with the residual block X '-X of reconstruct
ErAdd reference block X
Er, promptly obtain the non-ROI macro block X ' of reconstruct.
Beneficial effect: the present invention proposes a kind of distributed video decoding method that combines the wireless sensor network of area-of-interest extractive technique and residual error encoding and decoding technique advantage, be mainly used in the rate distortion characteristic that promotes distributed encoding and decoding system.
Based on turbo or LDPC to the indiscriminate encoding process of the All Ranges of Wyner-Ziv frame; For the more violent zone and the fringe region of motion object of moving; Motion estimation techniques can not accurately be predicted; Need so not only increase code check to the more feedback information of coding side request during decoding, and the parts of images of decoding is still accurate inadequately.And compress through the violent zone of ROI decision criteria extraction motion and based on entropy coding; All the other zones are then based on the distributed encoding and decoding of LDPC; Can strengthen the efficient of the fringe region coding of violent zone of motion and motion object; Thereby when reducing code check, improve decoded image quality, finally reduce the sensor node energy consumption.
Residual coding can make full use of the correlation of inter macroblocks, removes temporal redundancy.But when video flowing had bigger content change, the coded image that carries out residual coding operation and can be on the contrary was more complicated, and compression effectiveness receives very big loss.
The present invention utilizes the characteristics of extracting the distributed video encoding and decoding system of framework based on area-of-interest: this frame system is divided into piece with the W frame; Extract wherein the area-of-interest macro block fierce regional macro block that promptly moves and carry out entropy coding, wherein non-area-of-interest macro block carries out the LDPC encoding and decoding.But not the shortcoming of its application so take residual coding can make full use of the advantage of residual coding to this part macro block, is avoided in the area-of-interest not fierce zone of motion in the image/video sequence just.
Therefore, beneficial effect of the present invention mainly comprises the increase code efficiency, reduces code check, promotes picture quality, obtains better rate distortion characteristic, finally reduces the energy consumption of sensor node.
Description of drawings
Fig. 1 is based on the system block diagram of the distributed video encoding and decoding of area-of-interest extraction.
Fig. 2 is based on the W-Z frame encoding and decoding system block diagram of residual error encoding and decoding.
Fig. 3 is a distributed encoding and decoding block diagram of the present invention.
Fig. 4 is based on the flow chart of area-of-interest extraction algorithm.
Fig. 5 is a residual error code decode algorithm flow chart.
Fig. 6 is an algorithm flow chart of the present invention.
Embodiment
Basic framework of the present invention is based on the distributed coding system that area-of-interest extracts, and improved place is non-area-of-interest is taked residual coding, and the concrete operating procedure of this system is following:
Step 1. is divided into key frame (K) and Wyner-Ziv frame (W) with video flowing to be encoded.The K frame adopts the conventional coding scheme, the scheme that the W frame adopts LDPC encoding and decoding and entropy encoding/decoding to combine.
Step 2. is in the encoding scheme of coding side K frame employing JPEG, and the W frame is distinguished (area-of-interest differentiation) algorithm according to ROI, adopts the ROI judgment criterion that macro block is divided into ROI macro block and non-ROI macro block.
Step 3. pair ROI macro block is taked entropy encoding/decoding.
Step 4. is got reference block: the macro block X of current ROI macro block X and last key frame same position
Er
The macro block X of step 5. current ROI macro block X and last key frame same position
ErSubtract each other residual block X-X
Er
The step 6. pair residual block that produces carries out the LDPC coding.
Step 7. is in decoding end, and the ROI macro block is taked the mode of LDPC encoding and decoding, carries out the LDPC decoding to made difference gained residual block by non-ROI macro block and last key frame same position macro block.
The decoding side information of step 8. residual frame is to deduct X again by the side information Y that the K of reconstruct and W frame estimation interpolation produce
ErGained.
Step 9. adds residual frame X with the non-ROI piece of reconstruct at last
ErJust can obtain the non-ROI macro block of reconstruct.
Describe for ease, we have following application example at supposition, and as shown in Figure 3: system comprises the intraframe coding of K frame, K frame intraframe decoder, and W two field picture macro block discriminating module, ROI macro block entropy encoding/decoding is got residual block to non-ROI macro block work difference and is carried out the LDPC encoding and decoding.
Coding side, sensor node transmit a series of video sequences, and the postrun concrete steps of system are:
Step 1. marks off the K frame and the W frame of video sequence by the certain K frame and the distinguishing rule of W frame.
Step 2. pair K frame carries out intraframe coding.
The operation of step 3. pair W two field picture macro block discriminating module comprises:
(1) macro block interested extracts the operation of the comparison that is based on the quantization DCT coefficient difference.
(2) at first, the DCT coefficient of the current macro of current W-Z frame is compared with the DCT coefficient of the piece of last key frame same position.Obtain the difference d of quantization DCT coefficient
i
(3) with d
iBe defined as d
i=| q
i-h
i|, q wherein
iBe the DCT coefficient of the current macro of current W-Z frame, h
iQuantification DCT quantization parameter for the macro block of the last key frame that is stored in the coding side buffer and current macro same position current W-Z frame.
(4) the ROI judgment rule is following: max (d
i)＞1 perhaps
Be judged to be the ROI piece, other
Be non-ROI piece.R wherein
iBe according to the Zig-Zag scan mode and fixed weighted value, the weighted value of low frequency coefficient is greater than the weighted value of high frequency coefficient.In addition, i ∈ N represents the DCT coefficient number of current encoded frame.
Step 4. pair ROI macro block adopts entropy encoding/decoding.
The difference of same position macro block in non-ROI macro block and the key frame in the step 5. calculating W frame.
Step 6. pair this difference is carried out the LDPC coding.
Step 7. is through carrying out estimation to K frame and the W frame that reconstructs, and operation such as interpolation obtains the side information of LDPC decoding.But this side information will deduct the macro block that reference block is a same position in non-ROI macro block and the key frame.Obtain the difference side information.
Step 8. reconstructs residual block according to this difference side information.
Step 9. adds reference block with the residual block of reconstruct, promptly obtains the non-ROI macro block of reconstruct.
Step 10. is carried out the DCT inverse transformation at last, and combined decoding goes out the Wyner-Ziv frame.
Step 11. is recovered video sequence according to the K frame and the W frame that decode, accomplishes distributed encoding and decoding.
Claims (2)
1. distributed video decoding method that is applied to wireless sensor network is characterized in that the concrete steps of this method are:
Step 1. marks off the K frame and the W frame of video sequence,
Step 2. pair K frame carries out encoding and decoding in the frame,
The ROI macro block that step 3. selects a kind of area-of-interest extraction algorithm to distinguish in the W frame is the area-of-interest of image, refers to the more violent zone of motion in the image, with non-ROI macro block, is designated as X simultaneously;
Step 4. pair ROI macro block adopts entropy encoding/decoding;
Step 5. pair non-ROI macro block takes the residual error encoding and decoding promptly the residual error of image to be carried out encoding and decoding;
Step 6. is recovered video sequence according to the K frame and the W frame that decode, accomplishes distributed encoding and decoding.
2. the distributed video decoding method that is applied to wireless sensor network according to claim 1; It is characterized in that in the step 4; The ROI macro block is adopted entropy encoding/decoding, is that the prediction residual coding thinking is applied in the encoding and decoding of area-of-interest piece, and concrete steps are:
Same position macro block work difference X-X in non-ROI macro block and the key frame in the step 41. calculating W frame
Er, obtain residual image;
Step 42. pair this residual image carries out the LDPC coding;
Step 43. is through carrying out the side information Y that estimation obtains the LDPC decoding to K frame and the W frame that reconstructs; Side information Y deducts reference block X
ErBe the macro block that is positioned at same position in the key frame with non-ROI macro block, thereby obtain difference side information Y-X
Er
Step 44. reconstructs residual block X '-X according to this difference side information
Er
Step 45. is with the residual block X '-X of reconstruct
ErAdd reference block X
Er, promptly obtain the non-ROI macro block X ' of reconstruct.
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102833536A (en) * | 2012-07-24 | 2012-12-19 | 南京邮电大学 | Distributed video encoding and decoding method facing to wireless sensor network |
| CN102905129A (en) * | 2012-09-29 | 2013-01-30 | 湖北工业大学 | A Distributed Coding Method for Still Images |
| CN103067710A (en) * | 2012-12-28 | 2013-04-24 | 辽宁师范大学 | Distributed hyperspectral image coding and decoding method based on three-dimensional wavelet transform |
| CN103475879A (en) * | 2013-09-10 | 2013-12-25 | 南京邮电大学 | Side information generation method in distribution type video encoding |
| CN103702118A (en) * | 2014-01-02 | 2014-04-02 | 华为技术有限公司 | Image processing method and equipment |
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101005621A (en) * | 2007-01-11 | 2007-07-25 | 北京交通大学 | Distributive vide frequency coding method based self adaptive Hashenhege type vector quantization |
| US20080048895A1 (en) * | 2005-03-01 | 2008-02-28 | Zhixin Liu | Data Encoding and Decoding Using Slepian-Wolf Coded Nested Quantization to Achieve Wyner-Ziv Coding |
| CN101335892A (en) * | 2008-04-25 | 2008-12-31 | 太原科技大学 | Hybrid Distributed Video Coding Method Based on Intra Mode Decision |
| CN101835044A (en) * | 2010-04-23 | 2010-09-15 | 南京邮电大学 | A Classification and Combination Method in Frequency Domain Distributed Video Coding |
| CN101854548A (en) * | 2010-05-25 | 2010-10-06 | 南京邮电大学 | A video compression method for wireless multimedia sensor network |
-
2012
- 2012-02-17 CN CN2012100369341A patent/CN102595132A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20080048895A1 (en) * | 2005-03-01 | 2008-02-28 | Zhixin Liu | Data Encoding and Decoding Using Slepian-Wolf Coded Nested Quantization to Achieve Wyner-Ziv Coding |
| CN101005621A (en) * | 2007-01-11 | 2007-07-25 | 北京交通大学 | Distributive vide frequency coding method based self adaptive Hashenhege type vector quantization |
| CN101335892A (en) * | 2008-04-25 | 2008-12-31 | 太原科技大学 | Hybrid Distributed Video Coding Method Based on Intra Mode Decision |
| CN101835044A (en) * | 2010-04-23 | 2010-09-15 | 南京邮电大学 | A Classification and Combination Method in Frequency Domain Distributed Video Coding |
| CN101854548A (en) * | 2010-05-25 | 2010-10-06 | 南京邮电大学 | A video compression method for wireless multimedia sensor network |
Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102833536A (en) * | 2012-07-24 | 2012-12-19 | 南京邮电大学 | Distributed video encoding and decoding method facing to wireless sensor network |
| CN102905129A (en) * | 2012-09-29 | 2013-01-30 | 湖北工业大学 | A Distributed Coding Method for Still Images |
| CN102905129B (en) * | 2012-09-29 | 2015-03-18 | 湖北工业大学 | Distributed coding method of still image |
| CN103067710A (en) * | 2012-12-28 | 2013-04-24 | 辽宁师范大学 | Distributed hyperspectral image coding and decoding method based on three-dimensional wavelet transform |
| CN103067710B (en) * | 2012-12-28 | 2015-11-18 | 辽宁师范大学 | Based on distributed hyper spectrum image coding and the coding/decoding method of 3 D wavelet transformation |
| CN103974071A (en) * | 2013-01-29 | 2014-08-06 | 富士通株式会社 | Video coding method and equipment on basis of regions of interest |
| CN103475879A (en) * | 2013-09-10 | 2013-12-25 | 南京邮电大学 | Side information generation method in distribution type video encoding |
| CN103475879B (en) * | 2013-09-10 | 2016-06-01 | 南京邮电大学 | Limit information generating method in a kind of distributed video coding |
| CN103702118A (en) * | 2014-01-02 | 2014-04-02 | 华为技术有限公司 | Image processing method and equipment |
| CN106210744A (en) * | 2016-07-19 | 2016-12-07 | 华南农业大学 | Distributed residual video coding and decoding method based on macro block classification |
| CN106210744B (en) * | 2016-07-19 | 2019-01-08 | 华南农业大学 | Distributed residual video coding and decoding method based on macro block classification |
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Application publication date: 20120718 |