CN104952040A - Image filtering method and image filtering device - Google Patents
Image filtering method and image filtering device Download PDFInfo
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- CN104952040A CN104952040A CN201410116938.XA CN201410116938A CN104952040A CN 104952040 A CN104952040 A CN 104952040A CN 201410116938 A CN201410116938 A CN 201410116938A CN 104952040 A CN104952040 A CN 104952040A
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Abstract
An embodiment of the invention provides an image filtering method and an image filtering device. The image filtering method comprises the steps of dividing a to-be-processed image to a preset number of filtering blocks; determining a reference filtering block which matches a to-be-processed filtering block in the to-be-processed image in a reference image, wherein the to-be-processed filtering block is a random filtering block in the to-be-processed image; computing the motion intensity of the to-be-processed filtering block after spatial domain filtering by means of the reference filtering block after noise reduction, wherein the motion intensity represents the difference between the to-be-processed filtering block after spatial domain filtering and the reference filtering block after noise reduction; and when the motion intensity is smaller than a threshold value, performing time domain filtering on the to-be-processed filtering block after spatial domain filtering by means of the reference filtering block after noise reduction. The image filtering method and the image filtering device provided by the embodiment of the invention reduce a noise reduction processing difficulty and improve a noise reduction processing accuracy under a precondition that high image quality is ensured.
Description
Technical field
The application relates to technical field of image processing, relates to a kind of image filtering method and device in particular.
Background technology
Image may be subject to the interference of noise in the processes such as collection, transmission, and picture quality is reduced.Image filtering, namely refers to and to suppress the noise of image under the condition retaining image detail feature, be reduce picture noise, strengthen the important means of picture quality.
In prior art, image filtering method has two kinds usually: time-domain filtering and airspace filter, and time-domain filtering refers to the correlativity utilized between reference picture and pending image, utilizes the pixel of reference picture to reduce the noise in pending image; Airspace filter refers to by the correlativity in pending image between neighborhood pixels, uses neighborhood pixels to reduce the noise of object pixel.
But airspace filter mode just make use of the correlativity of image on spatial domain, filter effect, may the quality of effect diagram picture by certain restriction, and time-domain filtering mode utilizes reference picture to carry out noise reduction due to needs, adds the complexity of image noise reduction.
Summary of the invention
In view of this, this application provides a kind of image filtering method and device, improve image filtering effect, reduce the complexity of image noise reduction.
For achieving the above object, the application provides following technical scheme:
A kind of image filtering method, comprising:
Pending image is divided into the filter block of predetermined number;
Determine in reference picture, the reference filtering block mated with the pending filter block in described pending image, wherein, described pending filter block is arbitrary filter block in described pending image;
Utilize the reference filtering block after noise reduction, calculate the exercise intensity of the described pending filter block after airspace filter, wherein, described exercise intensity represents the diversity factor of the described pending filter block after airspace filter and the reference filtering block after described noise reduction;
When described exercise intensity is less than threshold value, utilize the reference filtering block of described noise reduction, time-domain filtering is carried out to the described pending filter block after airspace filter.
Preferably, describedly utilize the reference filtering block after noise reduction, the exercise intensity calculating the described pending filter block after airspace filter comprises:
Utilize the reference filtering block after airspace filter, calculate the exercise intensity of the described pending filter block after airspace filter.
Preferably, describedly determine in reference picture, the reference filtering block mated with the pending filter block in described pending image comprises:
Be divided into the filter block of predetermined number with reference to image, and airspace filter is carried out to each filter block;
Determine in described reference picture, mate with the pending filter block in described pending image, and carry out the reference filtering block after airspace filter.
Preferably, describedly determine in described reference picture, the reference filtering block mated with the pending filter block in described pending image comprises:
Each filter block in described pending image is carried out airspace filter;
Determine in described reference picture, the reference filtering block mated with the pending filter block after carrying out airspace filter in described pending image.
Preferably, utilize the reference filtering block after noise reduction, the exercise intensity calculating the described pending filter block after airspace filter comprises:
Described reference filtering block and described pending filter block are carried out airspace filter respectively;
Utilize the reference filtering block after carrying out airspace filter, calculate the exercise intensity of the described pending filter block after carrying out airspace filter.
A kind of image filtering device, comprising:
Block divides module, for pending image being divided into the filter block of predetermined number;
Matching module, for determining in reference picture, the reference filtering block mated with the pending filter block in described pending image, wherein, described pending filter block is arbitrary filter block in described pending image;
Strength co-mputation module, for utilizing the reference filtering block after noise reduction, calculate the exercise intensity of the described pending filter block after airspace filter, wherein, described exercise intensity represents the diversity factor of the described pending filter block after airspace filter and the reference filtering block after described noise reduction;
First filtration module, for when described exercise intensity is less than threshold value, utilizes the reference filtering block of described noise reduction, carries out time-domain filtering to the described pending filter block after airspace filter.
Preferably, described Strength co-mputation module, specifically for utilizing the reference filtering block after airspace filter, calculates the exercise intensity of the described pending filter block after airspace filter.
Preferably, described matching module comprises:
Second filtration module, for being divided into the filter block of predetermined number with reference to image, and carries out airspace filter to each filter block;
First matched sub-block, for determining in described reference picture, mates with the pending filter block in described pending image, and carries out the reference filtering block after airspace filter.
Preferably, described matching module comprises:
3rd filtration module, for carrying out airspace filter by each filter block in described pending image;
Second matched sub-block, for determining in described reference picture, the reference filtering block mated with the pending filter block after carrying out airspace filter in described pending image.
Preferably, described Strength co-mputation module comprises:
4th filtration module, for carrying out airspace filter respectively by described reference filtering block and described pending filter block;
Strength co-mputation submodule, for utilizing the reference filtering block after carrying out airspace filter, calculates the exercise intensity of the described pending filter block after carrying out airspace filter.
Known via above-mentioned technical scheme, compared with prior art, this application provides a kind of image filtering method and device, after pending image being divided into the filter block of predetermined number, determine in reference picture, the reference filtering block mated with pending filter block; Then utilize reference filtering block after noise reduction, calculate the exercise intensity of the pending filter block after carrying out airspace filter, and according to the size of exercise intensity, carry out time-domain filtering again to carrying out the pending filter block after airspace filter.According to different situations, comprehensive airspace filter and the time-domain filtering mode of using carries out image noise reduction, thus both can ensure the picture quality after noise reduction, can reduce again the complexity of image noise reduction process.
Accompanying drawing explanation
In order to be illustrated more clearly in the embodiment of the present application or technical scheme of the prior art, be briefly described to the accompanying drawing used required in embodiment or description of the prior art below, apparently, accompanying drawing in the following describes is only the embodiment of the application, for those of ordinary skill in the art, under the prerequisite not paying creative work, other accompanying drawing can also be obtained according to the accompanying drawing provided.
The process flow diagram of a kind of image filtering method embodiment that Fig. 1 provides for the embodiment of the present application;
The process flow diagram of a kind of another embodiment of image filtering method that Fig. 2 provides for the embodiment of the present application;
The process flow diagram of a kind of another embodiment of image filtering method that Fig. 3 provides for the embodiment of the present application;
The process flow diagram of a kind of another embodiment of image filtering method that Fig. 4 provides for the embodiment of the present application;
The structural representation of a kind of image filtering device embodiment that Fig. 5 provides for the embodiment of the present application;
The structural representation of a kind of another embodiment of image filtering device that Fig. 6 provides for the embodiment of the present application;
The structural representation of a kind of another embodiment of image filtering device that Fig. 7 provides for the embodiment of the present application;
The structural representation of a kind of another embodiment of image filtering device that Fig. 8 provides for the embodiment of the present application.
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present application, be clearly and completely described the technical scheme in the embodiment of the present application, obviously, described embodiment is only some embodiments of the present application, instead of whole embodiments.Based on the embodiment in the application, those of ordinary skill in the art are not making the every other embodiment obtained under creative work prerequisite, all belong to the scope of the application's protection.
In the embodiment of the present application, after pending image being divided into the filter block of predetermined number, determine in reference picture, the reference filtering block mated with pending filter block; Then utilize reference filtering block after noise reduction, calculate the exercise intensity of the pending filter block after carrying out airspace filter, and according to the size of exercise intensity, carry out time-domain filtering again to carrying out the pending filter block after airspace filter.First pending filter block is carried out airspace filter, improves the filter quality of pending filter block.And according to the diversity factor of the pending filter block after reference filtering block after noise reduction and airspace filter, when diversity factor is less, time-domain filtering is carried out again to carrying out the pending filter block after airspace filter, thus picture quality can be improved further, and the exercise intensity calculated more can accurately represent the diversity factor of the reference filtering block after noise reduction and the pending filter block after airspace filter, the accuracy of noise reduction process can be improved, reduce process errors, under the prerequisite ensureing picture quality, decrease the process complexity because error causes.
The process flow diagram of a kind of image filtering method embodiment that Fig. 1 provides for the embodiment of the present application, described method can comprise following step:
101: the filter block pending image being divided into predetermined number.
When carrying out image filtering, be block image being divided into non-overlapping copies, i.e. filter block, carries out filtering in units of filter block.
102: determine in reference picture, the reference filtering block mated with the pending filter block in described pending image.
Wherein, described pending filter block is the arbitrary filter block in described pending image.
Reference picture is the image with pending image similarity, in video image, this reference picture can refer in the previous frame image adjacent with pending image and a rear two field picture one or two.
Owing to being carry out filtering in units of filter block, pending filtering refers to any one filter block not carrying out filtering in pending image.
The reference filtering block mated with pending filter block in reference picture can refer to the parts of images with described pending filter block respective range region in reference picture, such as the image of m every trade pixel and n row row pixel, pending filter block is the parts of images that in pending image, xth row ~ xth+6 every trade pixel and y arrange the ~ the y+6 row row pixel, then namely reference filtering block can refer to that in reference picture, xth row ~ xth+6 every trade pixel and y arrange the parts of images of the ~ the y+6 row row pixel.
Certainly, when particularly reference picture is not a two field picture, this reference filtering block also can be determined according to certain matching principle, this matching principle defines the similarity degree of reference filtering block and pending filter block, therefore can according to matching principle, search in a reference image, to obtain the reference filtering block meeting matching principle.
103: utilize the reference filtering block after noise reduction, calculate the exercise intensity of the described pending filter block after airspace filter.
Wherein, the diversity factor of the reference filtering block of described exercise intensity after representing airspace filter after described pending filter block and described noise reduction.
104: when described exercise intensity is less than threshold value, utilize the reference filtering block of described noise reduction, time-domain filtering is carried out to the described pending filter block after airspace filter.
In the embodiment of the present application, first pending filter block carries out airspace filter, reduces the noise in pending filter block in airspace filter mode, because reference picture also may exist larger noise, therefore, in the embodiment of the present application, first reference filtering block also carries out noise reduction process.Reference filtering block after recycling noise reduction, calculate the exercise intensity of the pending filter block after airspace filter, make the exercise intensity calculated more can accurately represent the diversity factor of reference filtering block and pending filter block, the accuracy of noise processed can be improved, reduce process errors, decrease the process complexity because error causes.
To the pending filter block after airspace filter, according to the diversity factor of the reference filtering block after itself and noise reduction, determine whether to carry out time-domain filtering, to improve the quality of image.
The diversity factor of the reference filtering block after noise reduction and the pending filter block after airspace filter, determined by the exercise intensity of the pending filter block after airspace filter, if exercise intensity is less than threshold value, then show that the pending filter block difference after the reference filtering block after noise reduction and airspace filter is less, then can continue the described reference filtering block after utilizing noise reduction, time-domain filtering is carried out to the pending filter block after described airspace filter, thus the picture quality of pending filter block can be improved further.
And when if exercise intensity is greater than threshold value, then do not carry out time-domain filtering again to carrying out the pending filter block after airspace filter, avoid adopt time-domain filtering not only can not significantly improve picture quality, also add the problem of the complexity of algorithm.Carry out the pending filter block after airspace filter namely as the filter block after noise reduction process.
When exercise intensity equals threshold value, the described reference filtering block after noise reduction can be utilized, time-domain filtering is carried out to the pending filter block after described airspace filter; Or, no longer noise reduction process is carried out to the pending filter block after described airspace filter.
In the present embodiment, after pending image being divided into the filter block of predetermined number, first determine in reference picture, the reference filtering block mated with pending filter block; Then utilize reference filtering block after noise reduction, calculate the exercise intensity of the pending filter block after carrying out airspace filter, and according to the size of exercise intensity, carry out time-domain filtering again to carrying out the pending filter block after airspace filter.First pending filter block is carried out airspace filter, improves the filter quality of pending filter block.And according to the diversity factor of the pending filter block after reference filtering block after noise reduction and airspace filter, when diversity factor is less, time-domain filtering is carried out again to carrying out the pending filter block after airspace filter, thus picture quality can be improved further, and the exercise intensity calculated more can accurately represent the diversity factor of the reference filtering block after noise reduction and the pending filter block after airspace filter, the accuracy of noise reduction process can be improved, reduce process errors, under the prerequisite ensureing picture quality, decrease the process complexity because error causes.
Wherein, exercise intensity due to pending filter block represents the diversity factor of the reference filtering block after described pending filter block and described noise reduction, the calculating of this exercise intensity has multiple possibility implementation, in a kind of possibility implementation, the exercise intensity of pending filter block can calculate in the following manner:
MAD represents exercise intensity, and M*N represents the size of the filter block of division, M and N is expressed as the quantity of row pixel and row pixel, c
ijrepresent the pixel in pending filter block, p
ijrepresent the pixel in the reference filtering block after noise reduction.
Wherein, threshold value can be determined according to the noise criteria difference of image.
In addition, the noise reduction process of reference picture can adopt multiple implementation, in a kind of possibility implementation, airspace filter mode can be utilized to carry out noise reduction process to this reference picture, to reduce the noise of reference picture, improve the picture quality of reference picture.
The process flow diagram of a kind of another embodiment of image filtering method that Fig. 2 provides for the embodiment of the present application, described method can comprise following step:
201: the filter block pending image being divided into predetermined number.
202: the filter block being divided into predetermined number with reference to image, and airspace filter is carried out to each filter block.
203: determine in described reference picture, mate with the pending filter block in described pending image, and carry out the reference filtering block after airspace filter.
Wherein, described pending filter block is the arbitrary filter block in described pending image.
204: utilize the reference filtering block after airspace filter, calculate the exercise intensity of the described pending filter block after airspace filter.
Wherein, described exercise intensity represents the diversity factor of the described pending filter block after airspace filter and the reference filtering block after described noise reduction.
Wherein, after first pending filter block specifically can be carried out airspace filter by step 204; Then utilize the reference filtering block after airspace filter, calculate the exercise intensity of the described pending filter block after airspace filter.
Certainly, also after the filter block pending image being divided into predetermined number, filtering process can be carried out by each filter block.
Thus this step 203 can be mating with the pending filter block after carrying out airspace filter of determining, and carry out the reference filtering block after airspace filter.
205: when described exercise intensity is less than threshold value, utilize the reference filtering block of described noise reduction, time-domain filtering is carried out to the described pending filter block after airspace filter.
In the present embodiment, be divided into the filter block of described predetermined number with reference to image equally, and all carry out noise reduction process to each filter block, in the present embodiment, concrete employing is airspace filter mode.From but carry out the filter block after airspace filter from reference picture, the filter block mated with pending filter block of selection.
Each filter block with reference to image all carries out noise reduction process, to reduce the overall noise of reference picture, thus when carrying out pending image filtering, directly select the reference filtering block after the noise reduction of coupling, namely this reference filtering block is the filter block that picture quality is higher, thus the accuracy that pending filter block exercise intensity calculates, decrease process errors, improve picture quality further.
In the present embodiment, pending image and reference picture are all divided into the filter block of predetermined number, and airspace filter is carried out to each filter block in reference picture; Then determine in reference picture, the reference filtering block carrying out airspace filter mated with the pending filter block after carrying out airspace filter; Utilize the reference filtering block after airspace filter, calculate the exercise intensity carrying out the pending filter block after airspace filter, and according to the size of exercise intensity, carry out time-domain filtering to carrying out the pending filter block after airspace filter.First carry out airspace filter with reference to filter block and pending filter block, improve the filter quality of pending filter block.And according to the diversity factor of the pending filter block after airspace filter reference filtering block and airspace filter, determine whether to carry out time-domain filtering to carrying out the pending filter block after airspace filter again, thus picture quality can be improved further, and the exercise intensity calculated more can accurately represent the diversity factor of the reference filtering block after airspace filter and the pending filter block after airspace filter, the accuracy of noise reduction process can be improved, reduce process errors, under the prerequisite ensureing picture quality, decrease the process complexity because error causes.
The process flow diagram of a kind of another embodiment of image filtering method that Fig. 3 provides for the embodiment of the present application, described method can comprise following step:
301: the filter block pending image being divided into predetermined number.
302: each filter block in described pending image is carried out airspace filter;
303: determine in described reference picture, the reference filtering block mated with the pending filter block after carrying out airspace filter in described pending image.
Reference picture also can be divided into the filter block of predetermined number in advance.The parts of images of the respective range of mating with pending filter block also directly can searched in a reference image according to pending filter block is reference filtering block.
304: utilize the reference filtering block after airspace filter, calculate the exercise intensity of the described pending filter block after airspace filter.
Wherein, the diversity factor of the reference filtering block of described exercise intensity after representing airspace filter after described pending filter block and described airspace filter.
In step 304, first can carry out airspace filter with reference to filter block, and then utilize the reference filtering block after airspace filter, calculate the exercise intensity of the described pending filter block after airspace filter.
305: when described exercise intensity is less than threshold value, utilize the reference filtering block of described noise reduction, time-domain filtering is carried out to the described pending filter block after airspace filter.
The present embodiment, after pending image being divided into the filter block of predetermined number, by advanced for each filter block row airspace filter.Thus concrete determination is in reference picture, the reference filtering block mated with the pending filter block after carrying out airspace filter, thus the accuracy that can improve the reference filtering block determined further, be conducive to the picture quality improving pending filter block.
In the present embodiment, pending image and reference picture are all divided into the filter block of predetermined number, and airspace filter is carried out to each filter block in reference picture; Then determine in reference picture, the reference filtering block carrying out airspace filter mated with the pending filter block after carrying out airspace filter; Utilize the reference filtering block after airspace filter, calculate the exercise intensity carrying out the pending filter block after airspace filter, and according to the size of exercise intensity, carry out time-domain filtering to carrying out the pending filter block after airspace filter.First carry out airspace filter with reference to filter block and pending filter block, improve the filter quality of pending filter block.And according to the diversity factor of the pending filter block after airspace filter reference filtering block and airspace filter, determine whether to carry out time-domain filtering to carrying out the pending filter block after airspace filter again, thus picture quality can be improved further, and the exercise intensity calculated more can accurately represent the diversity factor of the reference filtering block after airspace filter and the pending filter block after airspace filter, the accuracy of noise reduction process can be improved, reduce process errors, under the prerequisite ensureing picture quality, decrease the process complexity because error causes.
The process flow diagram of a kind of another embodiment of image filtering method that Fig. 4 provides for the embodiment of the present application, described method can comprise following step:
401: the filter block pending image being divided into predetermined number.
402: determine in reference picture, the reference filtering block mated with the pending filter block in described pending image.
Wherein, this reference picture also can be divided into the filter block of predetermined number in advance.
Reference picture can be divided into the filter block of predetermined number in advance.The parts of images of the respective range of mating with pending filter block also directly can searched in a reference image according to pending filter block is reference filtering block.
403: described reference filtering block and described pending filter block are carried out airspace filter respectively.
404: utilize the reference filtering block after carrying out airspace filter, calculate the exercise intensity of the described pending filter block after carrying out airspace filter.
Wherein, described exercise intensity represents the difference of the described pending filter block after airspace filter and the reference filtering block after described airspace filter.
405: when described exercise intensity is less than threshold value, utilize the reference filtering block of described noise reduction, time-domain filtering is carried out to the described pending filter block after airspace filter.
In the present embodiment, after determining the reference filtering block that pending filter block is corresponding, respectively respectively airspace filter is carried out to reference filtering block and described pending filter block.
Owing to may not be that full content all as with reference to filter block, after therefore determining reference filtering block, then can carry out to it complexity that filtering can reduce noise reduction in reference picture, reduce operation steps.
In the present embodiment, pending image is divided into the filter block of predetermined number, and determines in reference picture, the reference filtering block mated with pending filter block; Then airspace filter is carried out with reference to filter block and pending filter block respectively; Utilize the reference filtering block after airspace filter, calculate the exercise intensity carrying out the pending filter block after airspace filter, and according to the size of exercise intensity, carry out time-domain filtering to carrying out the pending filter block after airspace filter.First carry out airspace filter with reference to filter block and pending filter block, improve the filter quality of pending filter block.And according to the diversity factor of the pending filter block after airspace filter reference filtering block and airspace filter, determine to carry out time-domain filtering to carrying out the pending filter block after airspace filter, thus picture quality can be improved further, and the exercise intensity calculated more can accurately represent the diversity factor of the reference filtering block after airspace filter and the pending filter block after airspace filter, the accuracy of noise reduction process can be improved, reduce process errors, under the prerequisite ensureing picture quality, decrease the process complexity because error causes
The embodiment of the present application application scenarios is in actual applications be applicable to the noise reduction of video image, and pending image is the two field picture in video, and reference picture can be and an adjacent frame of described pending image or two two field pictures.
For aforesaid each embodiment of the method, in order to simple description, therefore it is all expressed as a series of combination of actions, but those skilled in the art should know, the application is not by the restriction of described sequence of movement, because according to the application, some step can adopt other orders or carry out simultaneously.Secondly, those skilled in the art also should know, the embodiment described in instructions all belongs to preferred embodiment, and involved action and module might not be that the application is necessary.
The structural representation of a kind of image filtering device embodiment that Fig. 5 provides for the embodiment of the present application, described device can comprise:
Block divides module 501, for pending image being divided into the filter block of predetermined number.
Matching module 502, for determining in reference picture, the reference filtering block mated with the pending filter block in described pending image.
Wherein, described pending filter block is arbitrary filter block in described pending image.
Strength co-mputation module 503, for utilizing the reference filtering block after noise reduction, calculates the exercise intensity of the described pending filter block after airspace filter.
Wherein, described exercise intensity represents the difference of the described pending filter block after airspace filter and the reference filtering block after described noise reduction.
First filtration module 504, for when described exercise intensity is less than threshold value, utilizes the reference filtering block of described noise reduction, carries out time-domain filtering to the described pending filter block after airspace filter.
In the present embodiment, after pending image being divided into the filter block of predetermined number, first determine in reference picture, the reference filtering block mated with pending filter block; Then utilize reference filtering block after noise reduction, calculate the exercise intensity of the pending filter block after carrying out airspace filter, and according to the size of exercise intensity, carry out time-domain filtering again to carrying out the pending filter block after airspace filter.First pending filter block is carried out airspace filter, improves the filter quality of pending filter block.And according to the diversity factor of the pending filter block after reference filtering block after noise reduction and airspace filter, when diversity factor is less, time-domain filtering is carried out again to carrying out the pending filter block after airspace filter, thus picture quality can be improved further, and the exercise intensity calculated more can accurately represent the diversity factor of the reference filtering block after noise reduction and the pending filter block after airspace filter, the accuracy of noise reduction process can be improved, reduce process errors, under the prerequisite ensureing picture quality, decrease the process complexity because error causes.
Wherein, the calculating of exercise intensity has multiple possibility implementation, and in a kind of possibility implementation, the exercise intensity of pending filter block can calculate in the following manner:
MAD represents exercise intensity, and M*N represents the size of the filter block of division, M and N is respectively the value of row pixel and row pixel, c
ijrepresent the pixel in pending filter block, p
ijrepresent the pixel in the reference filtering block after noise reduction.
Wherein, threshold value can be determined according to the noise criteria difference of image.
In addition, the noise reduction process of reference picture can adopt multiple implementation, in a kind of possibility implementation, airspace filter mode can be utilized to carry out noise reduction process to this reference picture, to reduce the noise of reference picture, improve the picture quality of reference picture.
The structural representation of a kind of another embodiment of image filtering device that Fig. 6 provides for the embodiment of the present application, described device can comprise:
Block divides module 601, for pending image being divided into the filter block of predetermined number;
Matching module 602, for determining in reference picture, the reference filtering block mated with the pending filter block in described pending image.
Wherein, described pending filter block is arbitrary filter block in described pending image.
In the present embodiment, described matching module 602 can comprise:
Second filtration module 6021, for being divided into the filter block of predetermined number with reference to image, and carries out airspace filter to each filter block.
First matched sub-block 6022, for determining in described reference picture, mates with the pending filter block in described pending image, and carries out the reference filtering block after airspace filter.
Strength co-mputation module 603, for utilizing the reference filtering block after noise reduction, calculates the exercise intensity of the described pending filter block after airspace filter.
Wherein, described exercise intensity represents the diversity factor of the pending filter block after described airspace filter and the reference filtering block after described airspace filter.
First filtration module 604, for when described exercise intensity is less than threshold value, utilizes the reference filtering block of described noise reduction, carries out time-domain filtering to the described pending filter block after airspace filter.
In the present embodiment, be divided into the filter block of described predetermined number with reference to image equally, and all carry out noise reduction process to each filter block, in the present embodiment, concrete employing is airspace filter mode.
Each filter block with reference to image all carries out noise reduction process, to reduce the overall noise of reference picture, thus when carrying out pending image filtering, directly select the reference filtering block after the noise reduction of coupling, namely this reference filtering block is the filter block that picture quality is higher, thus the accuracy that pending filter block exercise intensity calculates, decrease process errors, improve picture quality further.
In the present embodiment, pending image and reference picture are all divided into the filter block of predetermined number, and airspace filter is carried out to each filter block in reference picture; Then determine in reference picture, the reference filtering block carrying out airspace filter mated with the pending filter block after carrying out airspace filter; Utilize the reference filtering block after airspace filter, calculate the exercise intensity carrying out the pending filter block after airspace filter, and according to the size of exercise intensity, carry out time-domain filtering to carrying out the pending filter block after airspace filter.First carry out airspace filter with reference to filter block and pending filter block, improve the filter quality of pending filter block.And according to the diversity factor of the pending filter block after airspace filter reference filtering block and airspace filter, determine whether to carry out time-domain filtering to carrying out the pending filter block after airspace filter again, thus picture quality can be improved further, and the exercise intensity calculated more can accurately represent the diversity factor of the reference filtering block after airspace filter and the pending filter block after airspace filter, the accuracy of noise reduction process can be improved, reduce process errors, under the prerequisite ensureing picture quality, decrease the process complexity because error causes.
The structural representation of a kind of another embodiment of image filtering device that Fig. 7 provides for the embodiment of the present application, described device can comprise:
Block divides module 701, for pending image being divided into the filter block of predetermined number;
Matching module 702, for determining in reference picture, the reference filtering block mated with the pending filter block in described pending image.
Wherein, described pending filter block is arbitrary filter block in described pending image.
In the present embodiment, this matching module 702 can comprise:
3rd filtration module 7021, for carrying out airspace filter by each filter block in described pending image.
Second matched sub-block 7022, for determining in described reference picture, the reference filtering block mated with the pending filter block after carrying out airspace filter in described pending image.
Reference picture also can be divided into the filter block of predetermined number in advance.The parts of images of the respective range of mating with pending filter block also directly can searched in a reference image according to pending filter block is reference filtering block.
Strength co-mputation module 703, for utilizing the reference filtering block after airspace filter, calculates the exercise intensity of the described pending filter block after airspace filter.
Wherein, described exercise intensity represents the diversity factor of the reference filtering block after described pending filter block and described noise reduction.
First filtration module 704, for when described exercise intensity is less than threshold value, utilizes the reference filtering block of described noise reduction, carries out time-domain filtering to the described pending filter block after airspace filter.
The present embodiment, after pending image being divided into the filter block of predetermined number, by advanced for each filter block row airspace filter.Thus concrete determination is in reference picture, the reference filtering block mated with the pending filter block after carrying out airspace filter, thus the accuracy that can improve the reference filtering block determined further, be conducive to the picture quality improving pending filter block.
The structural representation of a kind of another embodiment of image filtering device that Fig. 8 provides for the embodiment of the present application, described device can comprise:
Block divides module 801, for pending image being divided into the filter block of predetermined number.
Matching module 802, for determining in reference picture, the reference filtering block mated with the pending filter block in described pending image.
Wherein, described pending filter block is arbitrary filter block in described pending image.
Reference picture can be divided into the filter block of predetermined number in advance.The parts of images of the respective range of mating with pending filter block also directly can searched in a reference image according to pending filter block is reference filtering block.
Strength co-mputation module 803, for utilizing the reference filtering block after airspace filter, calculates the exercise intensity of the described pending filter block after airspace filter.
Wherein, described exercise intensity represents the diversity factor of the described pending filter block after airspace filter and the described reference filtering block after airspace filter.
In the present embodiment, this Strength co-mputation module 803 can comprise:
4th filtration module 8031, for carrying out airspace filter respectively by described reference filtering block and described pending filter block;
Strength co-mputation submodule 8032, for utilizing the reference filtering block after carrying out airspace filter, calculates the exercise intensity of the described pending filter block after carrying out airspace filter.
First filtration module 804, for when described exercise intensity is less than threshold value, utilizes the reference filtering block of described noise reduction, carries out time-domain filtering to the described pending filter block after airspace filter.
In the present embodiment, pending image is divided into the filter block of predetermined number, and determines in reference picture, the reference filtering block mated with pending filter block; Then airspace filter is carried out with reference to filter block and pending filter block respectively; Utilize the reference filtering block after airspace filter, calculate the exercise intensity carrying out the pending filter block after airspace filter, and according to the size of exercise intensity, carry out time-domain filtering to carrying out the pending filter block after airspace filter.First carry out airspace filter with reference to filter block and pending filter block, improve the filter quality of pending filter block.And according to the diversity factor of the pending filter block after airspace filter reference filtering block and airspace filter, determine to carry out time-domain filtering to carrying out the pending filter block after airspace filter, thus picture quality can be improved further, and the exercise intensity calculated more can accurately represent the diversity factor of the reference filtering block after airspace filter and the pending filter block after airspace filter, the accuracy of noise reduction process can be improved, reduce process errors, under the prerequisite ensureing picture quality, decrease the process complexity because error causes
In this instructions, each embodiment adopts the mode of going forward one by one to describe, and what each embodiment stressed is the difference with other embodiments, between each embodiment identical similar portion mutually see.For device disclosed in embodiment, because it corresponds to the method disclosed in Example, so description is fairly simple, relevant part illustrates see method part.
Finally, also it should be noted that, in this article, the such as relational terms of first and second grades and so on is only used for an entity or operation to separate with another entity or operational zone, and not necessarily requires or imply the relation that there is any this reality between these entities or operation or sequentially.And, term " comprises ", " comprising " or its any other variant are intended to contain comprising of nonexcludability, thus make to comprise the process of a series of key element, method, article or equipment and not only comprise those key elements, but also comprise other key elements clearly do not listed, or also comprise by the intrinsic key element of this process, method, article or equipment.When not more restrictions, the key element limited by statement " comprising ... ", and be not precluded within process, method, article or the equipment comprising described key element and also there is other identical element.
To the above-mentioned explanation of the disclosed embodiments, professional and technical personnel in the field are realized or uses the application.To be apparent for those skilled in the art to the multiple amendment of these embodiments, General Principle as defined herein when not departing from the spirit or scope of the application, can realize in other embodiments.Therefore, the application can not be restricted to these embodiments shown in this article, but will meet the widest scope consistent with principle disclosed herein and features of novelty.
Claims (10)
1. an image filtering method, is characterized in that, comprising:
Pending image is divided into the filter block of predetermined number;
Determine in reference picture, the reference filtering block mated with the pending filter block in described pending image, wherein, described pending filter block is arbitrary filter block in described pending image;
Utilize the reference filtering block after noise reduction, calculate the exercise intensity of the described pending filter block after airspace filter, wherein, described exercise intensity represents the diversity factor of the described pending filter block after airspace filter and the reference filtering block after described noise reduction;
When described exercise intensity is less than threshold value, utilize the reference filtering block of described noise reduction, time-domain filtering is carried out to the described pending filter block after airspace filter.
2. method according to claim 1, is characterized in that, describedly utilizes the reference filtering block after noise reduction, and the exercise intensity calculating the described pending filter block after airspace filter comprises:
Utilize the reference filtering block after airspace filter, calculate the exercise intensity of the described pending filter block after airspace filter.
3. method according to claim 2, is characterized in that, describedly determines in reference picture, and the reference filtering block mated with the pending filter block in described pending image comprises:
Be divided into the filter block of predetermined number with reference to image, and airspace filter is carried out to each filter block;
Determine in described reference picture, mate with the pending filter block in described pending image, and carry out the reference filtering block after airspace filter.
4. method according to claim 2, is characterized in that, describedly determines in described reference picture, and the reference filtering block mated with the pending filter block in described pending image comprises:
Each filter block in described pending image is carried out airspace filter;
Determine in described reference picture, the reference filtering block mated with the pending filter block after carrying out airspace filter in described pending image.
5. the method according to any one of claim 2, is characterized in that, utilizes the reference filtering block after noise reduction, and the exercise intensity calculating the described pending filter block after airspace filter comprises:
Described reference filtering block and described pending filter block are carried out airspace filter respectively;
Utilize the reference filtering block after carrying out airspace filter, calculate the exercise intensity of the described pending filter block after carrying out airspace filter.
6. an image filtering device, is characterized in that, comprising:
Block divides module, for pending image being divided into the filter block of predetermined number;
Matching module, for determining in reference picture, the reference filtering block mated with the pending filter block in described pending image, wherein, described pending filter block is arbitrary filter block in described pending image;
Strength co-mputation module, for utilizing the reference filtering block after noise reduction, calculate the exercise intensity of the described pending filter block after airspace filter, wherein, described exercise intensity represents the diversity factor of the described pending filter block after airspace filter and the reference filtering block after described noise reduction;
First filtration module, for when described exercise intensity is less than threshold value, utilizes the reference filtering block of described noise reduction, carries out time-domain filtering to the described pending filter block after airspace filter.
7. device according to claim 6, is characterized in that, described Strength co-mputation module, specifically for utilizing the reference filtering block after airspace filter, calculates the exercise intensity of the described pending filter block after airspace filter.
8. device according to claim 6, is characterized in that, described matching module comprises:
Second filtration module, for being divided into the filter block of predetermined number with reference to image, and carries out airspace filter to each filter block;
First matched sub-block, for determining in described reference picture, mates with the pending filter block in described pending image, and carries out the reference filtering block after airspace filter.
9. device according to claim 6, is characterized in that, described matching module comprises:
3rd filtration module, for carrying out airspace filter by each filter block in described pending image;
Second matched sub-block, for determining in described reference picture, the reference filtering block mated with the pending filter block after carrying out airspace filter in described pending image.
10. device according to claim 6, is characterized in that, described Strength co-mputation module comprises:
4th filtration module, for carrying out airspace filter respectively by described reference filtering block and described pending filter block;
Strength co-mputation submodule, for utilizing the reference filtering block after carrying out airspace filter, calculates the exercise intensity of the described pending filter block after carrying out airspace filter.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109978774A (en) * | 2017-12-27 | 2019-07-05 | 展讯通信（上海）有限公司 | Multiframe continuously waits the denoising fusion method and device of exposure images |
| WO2022206928A1 (en) * | 2021-04-01 | 2022-10-06 | Beijing Bytedance Network Technology Co., Ltd. | Method, device, and medium for video processing |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060146141A1 (en) * | 2004-12-17 | 2006-07-06 | Jun Xin | Method for randomly accessing multiview videos |
| CN102014240A (en) * | 2010-12-01 | 2011-04-13 | 深圳市蓝韵实业有限公司 | Real-time medical video image denoising method |
| CN102769722A (en) * | 2012-07-20 | 2012-11-07 | 上海富瀚微电子有限公司 | Time-space domain hybrid video noise reduction device and method |
| CN103606132A (en) * | 2013-10-31 | 2014-02-26 | 西安电子科技大学 | Multiframe digital image denoising method based on space domain and time domain combination filtering |
-
2014
- 2014-03-26 CN CN201410116938.XA patent/CN104952040A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060146141A1 (en) * | 2004-12-17 | 2006-07-06 | Jun Xin | Method for randomly accessing multiview videos |
| CN102014240A (en) * | 2010-12-01 | 2011-04-13 | 深圳市蓝韵实业有限公司 | Real-time medical video image denoising method |
| CN102769722A (en) * | 2012-07-20 | 2012-11-07 | 上海富瀚微电子有限公司 | Time-space domain hybrid video noise reduction device and method |
| CN103606132A (en) * | 2013-10-31 | 2014-02-26 | 西安电子科技大学 | Multiframe digital image denoising method based on space domain and time domain combination filtering |
Non-Patent Citations (3)
| Title |
|---|
| 孙文心等: "《军事海洋学引论》", 30 June 2011 * |
| 李岩等: "《基于运动补偿的自适应时域视频降噪算法研究》", 《半导体光电》 * |
| 龙红梅等: "《一种基于运动估计的3D视频降噪算法》", 《计算机与数字工程》 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109978774A (en) * | 2017-12-27 | 2019-07-05 | 展讯通信（上海）有限公司 | Multiframe continuously waits the denoising fusion method and device of exposure images |
| CN109978774B (en) * | 2017-12-27 | 2021-06-18 | 展讯通信（上海）有限公司 | Denoising fusion method and device for multi-frame continuous equal exposure images |
| WO2022206928A1 (en) * | 2021-04-01 | 2022-10-06 | Beijing Bytedance Network Technology Co., Ltd. | Method, device, and medium for video processing |
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