CN101771877B - Information processing method - Google Patents
Information processing method Download PDFInfo
- Publication number
- CN101771877B CN101771877B CN 201010034502 CN201010034502A CN101771877B CN 101771877 B CN101771877 B CN 101771877B CN 201010034502 CN201010034502 CN 201010034502 CN 201010034502 A CN201010034502 A CN 201010034502A CN 101771877 B CN101771877 B CN 101771877B
- Authority
- CN
- China
- Prior art keywords
- image
- resolution
- data
- weight coefficient
- low
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired - Fee Related
Links
Images
Landscapes
- Image Analysis (AREA)
- Image Processing (AREA)
Abstract
The invention discloses an information processing method for video coding and decoding, which comprises: before compressing and coding a high-resolution video image, decomposing the high-resolution video image into a plurality of low-resolution panoramic images, and generating a plurality of weighted images by summing the product of one of a plurality of low-resolution images with the same resolution and a first weighting coefficient and the products of the other low-resolution images and corresponding weighting coefficients in a second weighting coefficient group respectively; and using one of the plurality of weighted images as a basic reference image, improving an image quality on the basis of great reduction in the amount of information performing data compression coding, improvement in a coding efficiency and improvement in a video information transmitting efficiency by using one of the plurality of weighted images as a reference image after the coefficients of correlations between the other weighted images of the plurality of weighted images with the reference image are obtained by a correlativity analysis method, and solving the problem that an image edge is fuzzed to a certain extent. The information amount for data compression coding can be greatly reduced and the coding efficiency is enhanced.
Description
Technical field
The present invention relates to a kind of information processing method that is used for coding and decoding video, especially after original image information being decomposed into a plurality of low resolution similar image information, adopt the amount of information and raising information processing efficiency of similarity calculation method to reduce the follow-up coding/decoding; Belong to image/video coding/decoding technology field.
Background technology
Video coding and decoding technology is to realize high-quality, storage of low-cost multi-medium data and the key of transmitting efficiently.The image coding and decoding international standard of current trend all is based on so a kind of coding theory, the coding method that the motion compensation, discrete cosine transform and the quantification that are based on the piece coupling of employing combines.The international standards such as MPEG-1, MPEG-2 and MPEG-4 that typically have International Standards Organization/International Electrotechnical Commissio first United Technologies group to release.The AVS national standard of China's promulgation also is to adopt similar hybrid video coding strategy: modules such as prediction, conversion, quantification and comentropy coding.
The method of these video encoding standard process informations all is that original image is divided into a certain size block of information by the space, like the piece of 8X8, the piece of 16X16 etc.Do not have similitude between these block of informations, even therefore adopt the infra-frame prediction mode, its information prediction result can be not desirable.Can not effectively reduce frame internal information amount of redundancy.
The raising that Along with people's requires for picture quality, the resolution of image also improves constantly, and the corresponding information processing capacity that increases information encoding-decoding, has reduced every frame information processing speed, has promoted the requirement to transmission inromation bandwidth.
But in fact high resolution image frame internal information amount of redundancy is bigger.In image acquisition process, we have such result: obtain image with the IMAQ of low resolution and obtain image with IMAQ with high-resolution similitude is arranged.To obtain image with the IMAQ of high-resolution equally and have similitude through the image of the low resolution of extracted at equal intervals picture point information formation and the image of original high resolution.And also has similitude between the image of IMAQ acquisition image with high-resolution through a plurality of low resolution of extracted at equal intervals picture point information formation.These characteristics show that high-resolution image information inside is actually bigger information redundancy amount.Can handle through correlation with low-resolution image information and rebuild high-resolution image information.
The patent No. the applicant is ZL200610075904.6, and denomination of invention adopts the image similarity algorithm to reduce the method for information data amount for disclosing in the patent document of " a kind of image processing method that improves visual encoding-decoding efficiency " after high-definition picture is divided into the image of low resolution.But since this method with a width of cloth low-resolution image wherein as the reference image, in reality realizes, exist the profile of image by the problem of obfuscation, do not provide the method that is optimized between better pictures quality and the information data amount of how obtaining yet.Simultaneously owing to can't recover the different information of other width of cloth low-resolution images and reference image through the similitude algorithm as the reference image with a width of cloth low-resolution image wherein.
Summary of the invention
Technical problem to be solved by this invention is: propose a kind ofly high resolution video image is carried out compressed encoding to be decomposed into a plurality of low resolution panoramic pictures before handling; And after handling by a kind of algorithm of more optimizing; In the quality that reduces raising image on amount of information, raising code efficiency of carrying out data compression coding and the basis that promotes the video information efficiency of transmission greatly, and solve the image edge to a certain extent by the problem of obfuscation.。
First kind of technical scheme of the present invention is the system of selection that changes the reference image, and concrete scheme comprises
1, a kind of image processing method is characterized in that:
Information transmitting terminal comprises following steps:
1) the high resolution video image information that will handle adopts periodic sampling to generate the low-resolution image of several equal resolution;
2) calculate the weighted average image of the low-resolution image of said several equal resolution, identical or different to the weight coefficient that the low-resolution image of every width of cloth equal resolution is given, said weight coefficient be not less than 0 and the weight coefficient sum greater than 0;
3) be the reference image with said weighted average image; The low-resolution image that obtains said several equal resolution with correlation analysis respectively with the coefficient correlation of reference image, wherein said correlation analysis is linearity or nonlinear method;
4) said reference image and said coefficient correlation, said weight coefficient are perhaps sent data with said reference image and said coefficient correlation, said weight coefficient as information as the initial data of carrying out information processing;
Information receiving end comprises following steps:
5) receive that data are to carry out the data after the information processing or receive that data are reference image and coefficient correlation, said weight coefficient; When the data received after data are to carry out information processing, the corresponding processing method through said information processing obtains reference image and coefficient correlation, said weight coefficient;
6) calculate several low-resolution images according to said reference image and said coefficient correlation, said weight coefficient;
7) said several low-resolution images that calculate are reconfigured formation one panel height image in different resolution or said reference image and said several low-resolution images that calculate are reconfigured formation one panel height image in different resolution.
In the described step 1); Preferably said periodic sampling be by the row periodic sampling or by the row periodic sampling or simultaneously by row uniformly-spaced with by the row periodic sampling; Said by the row periodic sampling be single file uniformly-spaced or multirow uniformly-spaced, said by the row periodic sampling be uniformly-spaced single-row or multiple row uniformly-spaced.The low-resolution image that makes generation all is the low resolution panoramic picture of original image.Has visual similarity between the low-resolution image.
In the described step 3), preferably adopt correlation analysis to calculate the optimum coefficient correlation of all the other each low resolution image datas and reference view data.If adopt the Linear correlative analysis method, all the other each low resolution image datas can only be represented with two coefficients.For improving the precision of coefficient, can use coefficient of two byte representations, one of them byte representation coefficient integer part, another one byte representation fractional part.
In the described step 4), carrying out the follow-up image data processed is the coefficient correlation of reference image with all the other low resolution image datas of reflection that calculate of low resolution.Depositing in proper order of reference image and coefficient correlation can be made an appointment.Said information processing is to have one of known image compression encoding Processing Algorithm or combination now, like jpeg algorithm, MPEG algorithm, AVS algorithm etc.What optimize is that said information processing is handled the information lossless that is treated to of said coefficient correlation.
In the described step 5), at information receiving end, separating the view data that encoding process obtains through image decompressor is the coefficient correlation of reference image with several low resolution image datas of reflection of low resolution.Because reference image and coefficient correlation are to deposit by the order of depositing of making an appointment, and can extract respectively.
In the described step 6),, the reference image and the coefficient correlation of several low resolution image datas of reflection of the low resolution that obtains in the step 5) calculated the image of several low resolution at information receiving end.
In the described step 7),, the reference image of the low resolution that obtains in the step 6) and the image of several low resolution are reconfigured formation one panel height image in different resolution by the mode of making an appointment at information receiving end.Thereby effectively reproduce the original image information of transmitting terminal.This compound mode has multiple implementation method, and the image that first kind of mode is several low resolution makes up by the corresponding data of inserting of the sampling order of information transmitting terminal; The second way is to substitute the wherein image of a width of cloth low resolution with the reference image, makes up with the image of all the other low resolution corresponding insertion data of sampling order by information transmitting terminal then; The third mode is to adopt the inverse operation of weighted average calculation to calculate the calculated data of the image of original several low resolution reference image and image that calculates several low resolution and weight coefficient earlier, and the calculated data with the image that calculates original several low resolution makes up by the corresponding data of inserting of the sampling order of information transmitting terminal then.Mathematical descriptions is following:
The image that is set in several low resolution that information transmitting terminal generates be respectively Y1, Y2, Y3 ..., Yn; The weight coefficient of every width of cloth image be respectively K1, K2, K3 ..., Kn; Then weighted average image Y is:
Y＝(K1*Y1+K2*Y2+…+Kn*Yn)/(K1+K2+…+Kn)
With the weighted average image is the reference image, establishes the image of each width of cloth low resolution and the linearly dependent coefficient of reference image and is respectively r1, b1; R2, b2; Rn, bn.If the computed image of the image of several low resolution be respectively Y1 ', Y2 ', Y3 ' ..., Yn ', then:
Y1’＝r1*Y+b1
Y2’＝r2*Y+b2
………
Yn’＝rn*Y+bn
For first kind of mode be directly with Y1 ', Y2 ', Y3 ' ..., Yn ' makes up and obtains high rate image respectively by the corresponding data of inserting of the sampling of information transmitting terminal order; For the second way be earlier with Y replace Y1 ', Y2 ', Y3 ' ..., the width of cloth among the Yn '; Suppose to replace Y1 ', then with Y, Y2 ', Y3 ' ..., Yn ' makes up and obtains high rate image respectively by the corresponding data of inserting of the sampling of information transmitting terminal order; The third mode be Y1 ', Y2 ', Y3 ' ..., Yn ' regards the weighted average of original low-resolution image as, that is:
Y1’＝(K1*Y1”+K2*Y2”+…+Kn*Yn”)/(K1+K2+…+Kn)
Y2’＝(K1*Y1”+K2*Y2”+…+Kn*Yn”)/(K1+K2+…+Kn)
………
Yn’＝(K1*Y1”+K2*Y2”+…+Kn*Yn”)/(K1+K2+…+Kn)
Calculate Y1 through finding the solution above-mentioned equation group ", Y2 ", Y3 " ..., Yn ", then with Y1 ", Y2 ", Y3 " ..., Yn " make up and obtain high rate image respectively by the corresponding data of inserting of the sampling of information transmitting terminal order.
In such scheme because to adopt the weighted average image be the reference image; The data message that has comprised the low-resolution image of several equal resolution; Particularly there is partial information at the reference image for the part of the different information between the low-resolution image of several equal resolution; Therefore under the situation that the information data amount that information receiving end receives does not have to increase, improved combination and obtained the high quality of rate image respectively.
Second kind of technical scheme of the present invention is the weighted average image that carries out handling by different weight coefficients respectively the low-resolution image that obtains the every width of cloth equal resolution when changing the system of selection of reference image and with the low-resolution image of several equal resolution; Calculate the similitude between the weighted average image of low-resolution image of these equal resolution then; Improved the similitude between the image of participating in calculating, concrete scheme comprises:
1, a kind of image information processing method is characterized in that:
Information transmitting terminal comprises following steps:
1) the high resolution video image information that will handle adopts periodic sampling to generate the low-resolution image of several equal resolution;
2) set a plurality of weight coefficients; And set one of them weight coefficient greater than all the other weight coefficients; One of maximum is called first weight coefficient in said a plurality of weight coefficient; All the other weight coefficients are called the second weight coefficient group, and the data in the said second weight coefficient group are identical or different, and the corresponding relation of the said second weight coefficient group and every width of cloth low-resolution image is confirmed in advance; Said weight coefficient be not less than 0 and the weight coefficient sum greater than 0
3) low-resolution image of said several equal resolution multiply by first weight coefficient with a width of cloth low-resolution image wherein respectively and adds that all the other low-resolution images multiply by respectively in the second weight coefficient group and generate several weighted average images divided by the weight coefficient sum again behind the pairing weight coefficient;
4) with the wherein width of cloth of said several weighted average images as the reference image; All the other each width of cloth that obtain said several weighted average images with correlation analysis respectively with the coefficient correlation of reference image, wherein said correlation analysis is linearity or nonlinear method;
5) said reference image, said coefficient correlation, first weight coefficient and the second weight coefficient group are perhaps sent data with said reference image, said coefficient correlation, first weight coefficient and the second weight coefficient group as information as the initial data of carrying out information processing;
Information receiving end comprises following steps:
6) receive that data are to carry out the data after the information processing or receive that data are reference image, coefficient correlation, first weight coefficient and the second weight coefficient group; When the data received after data are to carry out information processing, the corresponding processing method through said information processing obtains reference image, coefficient correlation, first weight coefficient and second weight coefficient;
7) obtain several low-resolution images according to said reference image, said coefficient correlation, first weight coefficient and the second weight coefficient set of calculated and/or calculate the weighted average image of several low-resolution images;
8) the weighted average image of said several low-resolution images that calculate and/or several low-resolution images is reconfigured to form a panel height image in different resolution or said reference image and said several low-resolution images that calculate are reconfigured to form a panel height image in different resolution or the weighted average image of said reference image and said several low-resolution images that calculate reconfigured form a panel height image in different resolution.
Its neutral line similitude mathematical descriptions is following:
The image that is set in several low resolution that information transmitting terminal generates be respectively Y1, Y2, Y3 ..., Yn; Weight coefficient be respectively K1, K2, K3 ..., Kn; And set one of them weight coefficient greater than all the other weight coefficients; Be assumed to be K1; Be K1 greater than all the other weight coefficient K2, K3 ..., Kn, said weight coefficient K2, K3 ..., Kn and every width of cloth low-resolution image corresponding relation can confirm the weighted average image S1 of the image of then every width of cloth low resolution, S2 in advance ..., Sn:
S1＝(K1*Y1+K2*Y2+K3*Y3…+Kn*Yn)/(K1+K2+…+Kn)
S2＝(K1*Y2+K2*Y1+K3*Y3+…+Kn*Yn)/(K1+K2+…+Kn)
………
Sn＝(K1*Yn+Kn*Y1+K2*Y2+K3*Y3+…+K(n-1)*Y(n-1))/(K1+K2+…+Kn)
With weighted average image S1, S2 ..., among the Sn one for example is set at S1 as the reference image, calculates other weighted average images S2 ..., Sn and reference image linearly dependent coefficient be respectively r2, b2; R3, b3; Rn, bn.If the computed image of the image of several low resolution be respectively Y2 ', Y3 ' ..., Yn ', then:
Y2’＝r2*Y+b2
Y3’＝r3*Y+b3
………
Yn’＝rn*Y+bn
Can with S1, Y2 ', Y3 ' ..., Yn ' makes up and obtains high rate image respectively by the corresponding data of inserting of the sampling of information transmitting terminal order.Also can S1, Y2 ', Y3 ' ..., Yn ' regards the approximation of the weighted average image of original low-resolution image as, that is:
S1＝(K1*Y1”+K2*Y2”+K3*Y3”…+Kn*Yn”)/(K1+K2+…+Kn)
Y2’＝(K1*Y2”+K2*Y1”+K3*Y3”+…+Kn*Yn”)/(K1+K2+…+Kn)
Y3’＝(K1*Y3”+K3*Y1”+K2*Y2”+K4*Y4”+…+Kn*Yn”)/(K1+K2+…+Kn)
………
Yn’＝(K1*Yn”+Kn*Y1”+K2*Y2”+K3*Y3”+…+K (n-1)*Y(n-1)”)/(K1+K2+…+Kn)
Calculate Y1 through finding the solution above-mentioned equation group ", Y2 ", Y3 " ..., Yn ", then with Y1 ", Y2 ", Y3 " ..., Yn " make up and obtain high rate image respectively by the corresponding data of inserting of the sampling of information transmitting terminal order.
This scheme optimization scheme be weight coefficient be respectively K1, K2, K3 ..., Kn only gets two values, one of them is worth greater than another, promptly sets K1＞K2=K3=...=Kn.
In such scheme since calculate earlier every width of cloth low resolution image the weighted average image and improved the similitude of participating between the image that similitude calculates as the reference image with a width of cloth weighted average image wherein; And the linearisation degree is higher, is more suitable for linear dependence and calculates.The weighted average image of the image of every width of cloth low resolution has comprised the data message of the low-resolution image of several equal resolution; Particularly there is partial information at the weighted average image of the image of every width of cloth low resolution for the part of the different information between the low-resolution image of several equal resolution; Therefore under the situation that the information data amount that information receiving end receives does not have to increase, improved combination and obtained the high quality of rate image respectively.
The third technical scheme of the present invention is the weighted image that carries out handling by different weight coefficients respectively the low-resolution image that obtains the every width of cloth equal resolution when changing the system of selection of reference image and with the low-resolution image of several equal resolution; Calculate the similitude between the weighted image of low-resolution image of these equal resolution then; Improved the similitude between the image of participating in calculating, concrete scheme comprises:
1, a kind of information processing method is characterized in that:
Information transmitting terminal comprises following steps:
1) the high resolution video image information that will handle adopts periodic sampling to generate the low-resolution image of several equal resolution;
2) set a plurality of weight coefficients; And set one of them weight coefficient greater than all the other weight coefficients; One of maximum is called first weight coefficient in said a plurality of weight coefficient; All the other weight coefficients are called the second weight coefficient group, and the data in the said second weight coefficient group are identical or different, and the corresponding relation of the said second weight coefficient group and every width of cloth low-resolution image is confirmed in advance; Said weight coefficient be not less than 0 and the weight coefficient sum greater than 0
3) low-resolution image of said several equal resolution multiply by first weight coefficient with a width of cloth low-resolution image wherein respectively and adds that all the other low-resolution images multiply by that pairing weight coefficient generates several weighted images in the second weight coefficient group;
4) with the wherein width of cloth of said several weighted images as the reference image; All the other each width of cloth that obtain said several weighted images with correlation analysis respectively with the coefficient correlation of reference image, wherein said correlation analysis is linearity or nonlinear method;
5) said reference image, said coefficient correlation, first weight coefficient and the second weight coefficient group are perhaps sent data with said reference image, said coefficient correlation, first weight coefficient and the second weight coefficient group as information as the initial data of carrying out information processing;
Information receiving end comprises following steps:
6) receive that data are to carry out the data after the information processing or receive that data are reference image, coefficient correlation, first weight coefficient and the second weight coefficient group; When the data received after data are to carry out information processing, the corresponding processing method through said information processing obtains reference image, coefficient correlation, first weight coefficient and the second weight coefficient group;
7) obtain several low-resolution images according to said reference image, said coefficient correlation, first weight coefficient and the second weight coefficient set of calculated and/or calculate the weighted average image of several low-resolution images;
8) the weighted average image with said several low-resolution images that calculate and/or several low-resolution images reconfigures formation one panel height image in different resolution or said reference image is reconfigured formation one panel height image in different resolution divided by weighted average image and said several low-resolution images that calculate that the weight coefficient sum obtains.
Its neutral line similitude mathematical descriptions is following:
The image that is set in several low resolution that information transmitting terminal generates be respectively Y1, Y2, Y3 ..., Yn; Weight coefficient be respectively K1, K2, K3 ..., Kn; And set one of them weight coefficient greater than all the other weight coefficients; Be assumed to be K1, promptly K1 greater than all the other weight coefficient K2, K3 ..., Kn, the weighted image S1 of the image of then every width of cloth low resolution, S2 ..., Sn:
S1＝(K1*Y1+K2*Y2+K3*Y3…+Kn*Yn)
S2＝(K1*Y2+K2*Y1+K3*Y3+…+Kn*Yn)
………
Sn＝(K1*Yn+Kn*Y1+K2*Y2+K3*Y3+…+K(n-1)*Y(n-1))
With weighted image T1, T2 ..., among the Tn one for example is set at T1 as reference image Y, calculates other weighted images T2 ..., Tn and reference image linearly dependent coefficient be respectively r2, b2; R3, b3; Rn, bn.If the computed image of the image of several low resolution be respectively Y2 ', Y3 ' ..., Yn ', then:
Y2’＝r2*Y+b2
Y3’＝r3*Y+b3
………
Yn’＝rn*Y+bn
T1, Y2 ', Y3 ' ..., Yn ' regards the approximation of the weighted image of original low-resolution image as, that is:
T1＝(K1*Y1”+K2*Y2”+K3*Y3”…+Kn*Yn”)
Y2’＝(K1*Y2”+K2*Y1”+K3*Y3”+…+Kn*Yn”)
Y3’＝(K1*Y3”+K3*Y1”+K2*Y2”+K4*Y4”+…+Kn*Yn”)
………
Yn’＝(K1*Yn”+Kn*Y1”+K2*Y2”+K3*Y3”+…+K(n-1)*Y(n-1)”)
Calculate Y1 through finding the solution above-mentioned equation group ", Y2 ", Y3 " ..., Yn ", then with Y1 ", Y2 ", Y3 " ..., Yn " make up and obtain high rate image respectively by the corresponding data of inserting of the sampling of information transmitting terminal order.
Also can according to T1, Y2 ', Y3 ' ..., Yn ' calculates the weighted average image Y1 of several low-resolution images " ', Y2 " ', Y3 " ' ..., Yn " ' calculating formula is:
Y1”’＝T1/(K1+K2+K3+...+Kn)
Y2”＝Y2’/(K1+K2+K3+...+Kn)
Y3”’＝Y3/(K1+K2+K3+...+Kn)
………
Yn”’＝Yn’/(K1+K2+K3+...+KKn)
Then with Y1 " ', Y2 " ', Y3 " ' ..., Yn " ' make up and obtain high rate image respectively by the corresponding data of inserting of the sampling order of information transmitting terminal.
This scheme optimization scheme be weight coefficient be respectively K1, K2, K3 ..., Kn only gets two values, one of them is worth greater than another, promptly sets K1＞K2=K3=...=Kn.
When the third scheme satisfies K1+K2+K3+ ... During+Kn=1, the third scheme is consistent with first kind of scheme.
When the third scheme satisfies K1+K2+K3+ ... + Kn＞1 o'clock; The weighted image T1 of the image of every width of cloth low resolution, T2 ..., the data value of each pixel is enlarged among the Tn; Therefore need the more data position to come the data of remarked pixel point, so the data volume of the reference image that transmits of this scheme is greater than first kind of scheme and second kind of scheme.Such as working as K1+K2+K3+ ... During+Kn=256, the numerical value of each pixel is enlarged 256 times, and each color data amount of each pixel has increased a byte.But preferably work as K1+K2+K3+ ... + Kn was more than or equal to 256 o'clock, and what its image recovered is of high quality weighted image S1, S2 ..., the linear dependence between the Sn is very high.
Preferably K1, K2, K3 ..., size is close between the Kn, the linearity can improve, but when K1, K2, K3 ..., can cause the fuzzy of image edge when Kn equates basically.Preferably work as K1+K2+K3+ ... During+Kn=1, K1 gets between 0.3 to 0.4, K2=K3=... Between getting 0.2 to 0.3 ,=Kn can obtain the better image quality; Preferably work as K1+K2+K3+ ... During+Kn=256, K1 gets between 70 to 90, K2=K3=... Between getting 50 to 70 ,=Kn can obtain the better image quality
In such scheme since calculate earlier every width of cloth low resolution image weighted image and improved the similitude of participating between the image that similitude calculates as the reference image with a width of cloth weighted image wherein; And the linearisation degree is higher, is more suitable for linear dependence and calculates.The weighted image of the image of every width of cloth low resolution has comprised the data message of the low-resolution image of several equal resolution; Particularly there is partial information at every width of cloth weighted image for the part of the different information between the low-resolution image of several equal resolution; Therefore the amount of information that receives at information receiving end is more, has improved combination and has obtained the high quality of rate image respectively.
Be that example is described with the linear function fit in the mathematical description of such scheme, those skilled in the art can adopt other nonlinear functions carry out match with thought of the present invention fully, such as adopt secondary or more the curvilinear function of high order carry out match.
Before carrying out encoding compression processing, high resolution image data is formed the similar image of a plurality of low resolution through taking a sample at interval, adopt the correlation optimal algorithm to calculate the coefficient correlation of these low resolution similar images then.The coefficient correlation information of similar image that in information subsequent treatment and transmission, only needs image and other low resolution of a low resolution.Greatly reduce the data volume of message transmission, thereby improve image encoding compression efficiency and efficiency of transmission.Simultaneously for system of selection as the low-resolution image of reference image; Further improved the quality of the high-definition picture that is recovered; Reduced the fuzzy of image outline, edge etc., the correlation of carrying out between the image of correlation calculations is better, and the degree of deviation of data fitting is littler.Adopt the coefficient correlation of the similar image of a plurality of low resolution of correlation calculations, amount of calculation is few, and with respect to not adopting this technological image encoding and decoding technique, computational efficiency is higher.
Description of drawings
Fig. 1 is that the prior art view data that a 8X8 is big or small uniformly-spaced and by row periodic sampling data generates the big or small panoramic picture method example schematic diagram of 4 low resolution 4X4 by row.
Fig. 2 be prior art with the panoramic picture of 4 low resolution 4X4 sizes through the selection reference reference picture, calculate linearly dependent coefficient, deposit the method example schematic diagram of reference image and linear coefficient by about definite sequence.
Fig. 3 be the present invention with the panoramic picture of 4 low resolution 4X4 sizes through the selection reference reference picture, calculate linearly dependent coefficient, deposit first kind of realization of method sketch map of reference image and linear coefficient by about definite sequence.
Fig. 4 and Fig. 5 be the present invention with the panoramic picture of 4 low resolution 4X4 sizes through the selection reference reference picture, calculate linearly dependent coefficient, deposit second kind of realization of method sketch map of reference image and linear coefficient by about definite sequence.
Fig. 6 is the flow chart that first kind of technical scheme of the present invention is implemented in information transmitting terminal
First kind of technical scheme of Fig. 7 the present invention is implemented in the flow chart of information receiving end
Fig. 8 is the flow chart that second kind of technical scheme of the present invention is implemented in information transmitting terminal
Second kind of technical scheme of Fig. 9 the present invention is implemented in the flow chart of information receiving end
Figure 10 is the flow chart that the third technical scheme of the present invention is implemented in information transmitting terminal
The third technical scheme of Figure 11 the present invention is implemented in the flow chart of information receiving end
Embodiment
Below in conjunction with accompanying drawing and exemplifying embodiment to technical scheme further explain of the present invention:
Fig. 1 is that the prior art view data that a 8X8 is big or small uniformly-spaced and by row periodic sampling data generates the big or small panoramic picture method example schematic diagram of 4 low resolution 4X4 by row; Supposition high-resolution video raw image data is the data array of 8X8 among the figure, adopts interlacing to generate the low resolution image data of 4 4X4 sizes at a distance from row extracted at equal intervals data.The low resolution image data of these 4 4X4 sizes has comprised the total data of former 8X8 image.Such data pick-up method is that the low resolution image data of 4 4X4 sizes has very strong visual similarity.And wherein the low resolution image data of any one 4X4 size all is to extract from original image uniformly, also has visual similarity with original image.
Fig. 2 be prior art with the panoramic picture of 4 low resolution 4X4 sizes through the selection reference reference picture, calculate linearly dependent coefficient, deposit the method example schematic diagram of reference image and linear coefficient by about definite sequence.In the drawings; The panoramic picture of our selected first low resolution 4X4 size calculates the panoramic picture of all the other low resolution 4X4 sizes and optimum linearity coefficient correlation S1, S2, S3, S4, S5, the S6 of reference image respectively then as the reference image.Reference array of image data and linearly dependent coefficient S1, S2, S3, S4, S5, S6 are deposited the new data array 6X4 size of formation by the order of depositing of making an appointment.This 6X4 size data array is the primary data information (pdi) that image carries out the subsequent compression coding.Obviously need compressed encoding information processed amount to significantly reduce.
Method owing to the selection reference reference picture in the prior art is from several low resolution panoramic pictures, to select a width of cloth; When the profile of image or edge are very tiny; Such as in image, a line segment or a curve that a pixel thickness is only arranged being arranged; Because when the high-definition picture periodic sampling is generated the low resolution panoramic picture; Line segment that these are tiny or curve data can not appear in several low resolution panoramic pictures simultaneously, select any width of cloth low resolution panoramic picture all can't recover the full detail of line segment or curve through the relevance algorithms of prior art, occur therefore that the edge is fuzzy, the unsharp situation of profile.
Fig. 3 be the present invention with the panoramic picture of 4 low resolution 4X4 sizes through the selection reference reference picture, calculate linearly dependent coefficient, deposit first kind of realization of method sketch map of reference image and linear coefficient by about definite sequence.Than prior art, carried out special processing for the selection of reference image in first kind of realization of the present invention.Be the information that the information of reference image has comprised every width of cloth low resolution panoramic picture, can recover the whole profile informations and the side information of high-definition picture in calculating basically carrying out similitude.The special processing of said reference image can be adopted as every width of cloth low resolution panoramic picture and give similar and different weight coefficient, calculates the respective pixel dot information of the weighted average of each pixel as the reference image then.Calculating formula such as the pixel b11 of the reference image among Fig. 3 is following:
b11＝(K1*a11+K2*a12+K3*a21+K4*a22)/(K1+K2+K3+K4)
Wherein K1, K2, K3, K4 are weight coefficient, and the value of K1, K2, K3, K4 is that nonnegative number and weight coefficient sum are greater than 0.The selection of optimizing is K1=K2=K3=K4 and K1+K2+K3+K4=1.
Fig. 6 is the flow chart that first kind of technical scheme of the present invention is implemented in information transmitting terminal.Reference image-selecting method corresponding to Fig. 3 is illustrated in information transmitting terminal among the figure, carry out compressed encoding again after high resolution image data is accomplished by following treatment step.
For information transmitting terminal: obtain the high resolution video image data array in step 601; Generate several low resolution image data arrays through step 602 by going uniformly-spaced and pressing the row periodic sampling; Then step 603 calculate said several resolution low-resolution image the weighted average image and during in step 604 with the weighted average image as the reference view data; In step 605, calculate subsequently all the other low-resolution video view data respectively with the optimum linearity coefficient of reference view data, in step 606, the linearly dependent coefficient of reference view data and all the other low-resolution images is deposited back entering step 607 subsequent compression encoding process by about definite sequence at last.
First kind of technical scheme of Fig. 7 the present invention is implemented in the flow chart of information receiving end.Reference image-selecting method corresponding to Fig. 3; Be illustrated in information receiving end among the figure; The data message that will pass through decoding decompression acquisition is the coefficient correlation of reference image data information and all the other low resolution image datas, could generate a panel height resolution video image data message after accomplishing by following treatment step.
For information receiving end, the data after step 701 decompresses through decoding are deposited the linearly dependent coefficient that order obtains reference view data and all the other low-resolution images through step 702 by appointed information; In step 703, calculate all the other low-resolution video view data then and in step 704, confirm the sampling order of reference view data and all the other low-resolution video view data with reference view data and linearly dependent coefficient; In step 705, uniformly-spaced insert data mode with the reference view data with a plurality of low resolution image data array synthesizes the high resolution video image data and in step 706, reproduce the high resolution video image data array at last by ranks.
Because decomposing by method of the present invention between the low-resolution image of generation, high resolution image data exists bigger visual similarity; And adopt and to carry out weighted average to all low-resolution images and calculate and choose the reference image; Make corresponding view data have the better linearity correlation and make the edge and profile information partly is restored; Therefore in information Compression and transmission, can only need to handle and transmit the data of a reference image and the coefficient correlation of other low resolution image datas gets final product; Thereby reduce the information data amount of subsequent treatment greatly, make Information Compression, encoding and decoding and efficiency of transmission higher.
Fig. 4 and Fig. 5 be the present invention with the panoramic picture of 4 low resolution 4X4 sizes through the selection reference reference picture, calculate linearly dependent coefficient, deposit second kind of realization of method sketch map of reference image and linear coefficient by about definite sequence.Than prior art; Not only carried out special processing in second kind of realization of the present invention, and carried out handling to improve the correlation between the low-resolution image of participating in calculating for the low-resolution image of participating in similitude calculating for the selection of reference image.Panoramic picture with 4 low resolution 4X4 sizes in Fig. 4 calculates the weighted average image respectively as follows:
Set four weight coefficient K1, K2, K3, K4 wherein K1 greater than all the other weight coefficient K2, K3, K4; The corresponding relation of said weight coefficient K2, K3, K4 and every width of cloth low-resolution image can confirm in advance, and the value of K1, K2, K3, K4 is that nonnegative number and weight coefficient sum are greater than 0.The weighted average image B 1 of the image of then every width of cloth low resolution, B2, B3, B4:
B1＝(K1*Y1+K2*Y2+K3*Y3+K4*Y4)/(K1+K2+K3+K4)
B2＝(K1*Y2+K2*Y1+K3*Y3+K4*Y4)/(K1+K2+K3+K4)
B3＝(K1*Y3+K3*Y1+K2*Y2+K4*Y4)/(K1+K2+K3+K4)
B4＝(K1*Y4+K4*Y1+K2*Y2+K3*Y4)/(K1+K2+K3+K4)
For example, the image data information of weighted average image B 1 pixel b11 is calculated by following among Fig. 4:
b11＝(K1*a11+K2*a12+K3*a21+K4*a22)/(K1+K2+K3+K4)
For example, the image data information of weighted average image B 2 pixel b12 is calculated by following among Fig. 4:
b12＝(K1*a12+K2*a11+K3*a21+K4*a22)/(K1+K2+K3+K4)
For example, the image data information of weighted average image B 3 pixel b21 is calculated by following among Fig. 4:
b21＝(K1*a21+K3*a11+K2*a12+K4*a22)/(K1+K2+K3+K4)
For example, the image data information of weighted average image B 4 pixel b22 is calculated by following among Fig. 4:
b22＝(K1*a22+K4*a11+K2*a12+K3*a21)/(K1+K2+K3+K4)
In Fig. 5, select a seat reference image among weighted average image B 1, B2, B3, the B4 then,, calculate all the other weighted average image B 2, B3, B4 item coefficient correlation S1, S2, S3, S4 then for reference figure B1 such as selecting B1.The information that need carry out the follow-up processed compressed comprise reference figure B1 and coefficient correlation S1, S2, S3, S4 altogether the data message amount be the 6X4 size, can recover the whole profile informations and the side information of high-definition picture in calculating basically carrying out similitude.
Fig. 8 is the flow chart that second kind of technical scheme of the present invention is implemented in information transmitting terminal.Reference image-selecting method corresponding to Fig. 4, Fig. 5 is illustrated in information transmitting terminal among the figure, carry out compressed encoding again after high resolution image data is accomplished by following treatment step.
For information transmitting terminal: obtain the high resolution video image data array in step 801; Through step 802 by row uniformly-spaced and press low-resolution image Y1 that the row periodic sampling generates n width of cloth equal resolution, Y2 ..., Yn; In step 803, set the first weight coefficient K1 and the second weight coefficient K2; The said first weight coefficient K1 is greater than the said second weight coefficient K2; Generate n width of cloth weighted average image in step 804 by calculating formula Bi=((K1-K2) * Yi+K2* (Y1+Y2+......+Yn))/(K1+ (n-1) * K2) then; And when step 805 with a width of cloth weighted average image wherein as the reference view data; In step 806, calculate subsequently all the other weighted average view data respectively with the optimum linearity coefficient of reference view data, in step 807, the linearly dependent coefficient of reference view data and all the other weighted average images is deposited back entering step 808 subsequent compression encoding process by about definite sequence at last.
Second kind of technical scheme of Fig. 9 the present invention is implemented in the flow chart of information receiving end.Reference image-selecting method corresponding to Fig. 4, Fig. 5; Be illustrated in information receiving end among the figure; The data message that will pass through decoding decompression acquisition is the coefficient correlation of reference image data information and all the other weighted average images, could generate a panel height resolution video image data message after accomplishing by following treatment step.
For information receiving end, the data after step 901 decompresses through decoding are deposited the linearly dependent coefficient that order obtains reference view data and all the other weighted average images through step 902 by appointed information; The sampling of in step 903, calculating all the other weighted average view data with reference view data and linearly dependent coefficient then and in step 904, calculating a plurality of low resolution image datas with reference view data and all the other weighted average view data and in step 905, confirming reference view data and a plurality of low resolution image datas in proper order; In step 906, uniformly-spaced insert data mode with the reference view data with a plurality of low resolution image data array synthesizes the high resolution video image data and in step 907, reproduce the high resolution video image data array at last by ranks.
Because decomposing by method of the present invention between the low-resolution image of generation, high resolution image data exists bigger visual similarity; And adopt and to carry out weighted average to all low-resolution images and calculate several weighted average images and therefrom select a width of cloth as choosing the reference image; Make corresponding several weighted average view data have the better linearity correlation and make the edge and profile information partly is restored; Therefore in information Compression and transmission, can only need to handle and transmit the data of a reference image and the coefficient correlation of other several weighted average view data gets final product; Thereby reduce the information data amount of subsequent treatment greatly, make Information Compression, encoding and decoding and efficiency of transmission higher.
Figure 10 is the flow chart that the third technical scheme of the present invention is implemented in information transmitting terminal.Be illustrated in information transmitting terminal among the figure, carry out compressed encoding again after high resolution image data is accomplished by following treatment step.
For information transmitting terminal: obtain the high resolution video image data array in step 1001; Through step 1002 by row uniformly-spaced and press low-resolution image Y1 that the row periodic sampling generates n width of cloth equal resolution, Y2 ..., Yn; In step 1003, set the first weight coefficient K1 and the second weight coefficient K2; The said first weight coefficient K1 is greater than the said second weight coefficient K2; Generate n width of cloth weighted image in step 1004 by calculating formula Yi=(K1-K2) * Yi+K2* (Y1+Y2+......+Yn) then; And when step 1005 with a width of cloth weighted image wherein as the reference view data; In step 1006, calculate subsequently all the other weighted image data respectively with the optimum linearity coefficient of reference view data, in step 1007, the linearly dependent coefficient of reference view data and all the other weighted images is deposited back entering step 1008 subsequent compression encoding process by about definite sequence at last.
Second kind of technical scheme of Figure 11 the present invention is implemented in the flow chart of information receiving end.Be illustrated in information receiving end among the figure, the data message that will pass through decoding decompression acquisition is the coefficient correlation of reference image data information and all the other weighted images, could generate a panel height resolution video image data message after accomplishing by following treatment step.
For information receiving end, the data after step 1101 decompresses through decoding are deposited the linearly dependent coefficient that order obtains reference view data and all the other weighted images through step 1102 by appointed information; In step 1103, calculate all the other weighted image data then and in step 1104, obtain several low-resolution images and definite sampling order of calculating resultant several low resolution image datas in step 1105 with reference view data and all the other weighted image data computation with reference view data and linearly dependent coefficient; Insert uniformly-spaced by ranks in step 1106 at last that data mode will calculate that resultant several low resolution image datas synthesize the high resolution video image data and in step 1107, reproduce the high resolution video image data array.
Because decomposing by method of the present invention between the low-resolution image of generation, high resolution image data exists bigger visual similarity; And adopt and to carry out weighted calculation to all low-resolution images and obtain several weighted images and therefrom select a width of cloth as choosing the reference image; Make corresponding several weighted image data have the better linearity correlation and make the edge and profile information partly is restored; Therefore in information Compression and transmission, can only need to handle and transmit the data of a reference image and the coefficient correlation of other several weighted image data gets final product; Thereby reduce the information data amount of subsequent treatment greatly, make Information Compression, encoding and decoding and efficiency of transmission higher.
Claims (10)
1. information processing method is characterized in that:
Information transmitting terminal comprises following steps:
1) the high resolution video image information that will handle adopts periodic sampling to generate the low-resolution image of several equal resolution;
2) set a plurality of weight coefficients; And set one of them weight coefficient greater than all the other weight coefficients; One of maximum is called first weight coefficient in said a plurality of weight coefficient; All the other weight coefficients are called the second weight coefficient group, and the data in the said second weight coefficient group are identical or different, and the corresponding relation of the said second weight coefficient group and every width of cloth low-resolution image is confirmed in advance;
3) low-resolution image of said several equal resolution multiply by first weight coefficient with a width of cloth low-resolution image wherein respectively and adds that all the other low-resolution images multiply by that pairing weight coefficient generates several weighted images in the second weight coefficient group;
4) with the wherein width of cloth of said several weighted images as the reference image; All the other each width of cloth that obtain said several weighted images with correlation analysis respectively with the coefficient correlation of reference image, wherein said correlation analysis is linearity or nonlinear method;
5) said reference image, said coefficient correlation, first weight coefficient and the second weight coefficient group are perhaps sent data with said reference image, said coefficient correlation, first weight coefficient and the second weight coefficient group as information as the initial data of carrying out information processing;
Information receiving end comprises following steps:
6) receive that data are to carry out the data after the information processing or receive that data are reference image, coefficient correlation, first weight coefficient and the second weight coefficient group; When the data received after data are to carry out information processing, the corresponding processing method through said information processing obtains reference image, coefficient correlation, first weight coefficient and the second weight coefficient group;
7) obtain several low-resolution images according to said reference image, said coefficient correlation, first weight coefficient and the second weight coefficient set of calculated and/or calculate the weighted average image of several low-resolution images;
8) the weighted average image with said several low-resolution images that calculate and/or several low-resolution images reconfigures formation one panel height image in different resolution or said reference image is reconfigured formation one panel height image in different resolution divided by weighted average image and said several low-resolution images that calculate that said weight coefficient sum obtains.
2. information processing method according to claim 1; It is characterized in that in the described step 1); Said periodic sampling be by the row periodic sampling or by the row periodic sampling or simultaneously by row uniformly-spaced with by the row periodic sampling; Said by the row periodic sampling be single file uniformly-spaced or multirow uniformly-spaced, said by the row periodic sampling be uniformly-spaced single-row or multiple row uniformly-spaced.
3. information processing method according to claim 1 is characterized in that in the said step 4), when said correlation analysis is linear method, calculates the optimum linearity coefficient correlation of all the other each weighted image data and reference view data.
4. information processing method according to claim 1 is characterized in that in the described step 8), and the image of said several low resolution that calculate makes up by the corresponding data of inserting of sampling order that information transmitting terminal generates several low-resolution images; The weighted average image of perhaps said several low-resolution images that calculate makes up by the corresponding data of inserting of sampling order that information transmitting terminal generates several low-resolution images; Perhaps earlier with reference image, weight coefficient with calculate several weighted images and adopt the inverse operation of weighted calculation to calculate the calculated data of the image of original several low resolution, the calculated data with the image that calculates original several low resolution makes up by the corresponding data of inserting of sampling order that information transmitting terminal generates several low-resolution images then.
5. information processing method according to claim 2 is characterized in that in the said step 4), when said correlation analysis is linear method, calculates the optimum linearity coefficient correlation of all the other each weighted image data and reference view data.
6. information processing method according to claim 2 is characterized in that in the described step 8), and the image of said several low resolution that calculate makes up by the corresponding data of inserting of sampling order that information transmitting terminal generates several low-resolution images; The weighted average image of perhaps said several low-resolution images that calculate makes up by the corresponding data of inserting of sampling order that information transmitting terminal generates several low-resolution images; Perhaps earlier with reference image, weight coefficient with calculate several weighted images and adopt the inverse operation of weighted calculation to calculate the calculated data of the image of original several low resolution, the calculated data with the image that calculates original several low resolution makes up by the corresponding data of inserting of sampling order that information transmitting terminal generates several low-resolution images then.
7. information processing method according to claim 3 is characterized in that in the described step 8), and the image of said several low resolution that calculate makes up by the corresponding data of inserting of sampling order that information transmitting terminal generates several low-resolution images; The weighted average image of perhaps said several low-resolution images that calculate makes up by the corresponding data of inserting of sampling order that information transmitting terminal generates several low-resolution images; Perhaps earlier with reference image, weight coefficient with calculate several weighted images and adopt the inverse operation of weighted calculation to calculate the calculated data of the image of original several low resolution, the calculated data with the image that calculates original several low resolution makes up by the corresponding data of inserting of sampling order that information transmitting terminal generates several low-resolution images then.
8. information processing method according to claim 5 is characterized in that in the described step 8), and the image of said several low resolution that calculate makes up by the corresponding data of inserting of sampling order that information transmitting terminal generates several low-resolution images; The weighted average image of perhaps said several low-resolution images that calculate makes up by the corresponding data of inserting of sampling order that information transmitting terminal generates several low-resolution images; Perhaps earlier with reference image, weight coefficient with calculate several weighted images and adopt the inverse operation of weighted calculation to calculate the calculated data of the image of original several low resolution, the calculated data with the image that calculates original several low resolution makes up by the corresponding data of inserting of sampling order that information transmitting terminal generates several low-resolution images then.
9. according to each described information processing method in the claim 1 to 8, it is characterized in that said reference image and said coefficient correlation to deposit order be to make an appointment.
10. according to each described information processing method in the claim 1 to 8, it is characterized in that the information processing in the said step 5) comprises the coding computing of image; The corresponding processing method of the information processing in the said step 6) comprises decoding operation.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN 201010034502 CN101771877B (en) | 2010-01-20 | 2010-01-20 | Information processing method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN 201010034502 CN101771877B (en) | 2010-01-20 | 2010-01-20 | Information processing method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN101771877A CN101771877A (en) | 2010-07-07 |
| CN101771877B true CN101771877B (en) | 2012-07-25 |
Family
ID=42504422
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN 201010034502 Expired - Fee Related CN101771877B (en) | 2010-01-20 | 2010-01-20 | Information processing method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN101771877B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107409233A (en) * | 2015-03-05 | 2017-11-28 | 索尼公司 | Image processing apparatus and image processing method |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1276946A (en) * | 1997-12-23 | 2000-12-13 | 汤姆森特许公司 | Low noise encoding and decoding method |
| CN1852440A (en) * | 2006-04-24 | 2006-10-25 | 李博航 | Image processing method of increasing information encoding-decoding efficiency |
| CN101478672A (en) * | 2008-01-04 | 2009-07-08 | 华为技术有限公司 | Video encoding, decoding method and apparatus, video processing system |
-
2010
- 2010-01-20 CN CN 201010034502 patent/CN101771877B/en not_active Expired - Fee Related
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1276946A (en) * | 1997-12-23 | 2000-12-13 | 汤姆森特许公司 | Low noise encoding and decoding method |
| CN1852440A (en) * | 2006-04-24 | 2006-10-25 | 李博航 | Image processing method of increasing information encoding-decoding efficiency |
| CN101478672A (en) * | 2008-01-04 | 2009-07-08 | 华为技术有限公司 | Video encoding, decoding method and apparatus, video processing system |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107409233A (en) * | 2015-03-05 | 2017-11-28 | 索尼公司 | Image processing apparatus and image processing method |
| CN107409233B (en) * | 2015-03-05 | 2020-04-14 | 索尼公司 | Image processing apparatus, image processing method, and program |
Also Published As
| Publication number | Publication date |
|---|---|
| CN101771877A (en) | 2010-07-07 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11259031B2 (en) | Image processing method, device, and system | |
| AU2013261843B2 (en) | Decomposition of residual data during signal encoding, decoding and reconstruction in a tiered hierarchy | |
| US8750383B2 (en) | Systems and methods for wavelet and channel-based high definition video encoding | |
| Taquet et al. | Hierarchical oriented predictions for resolution scalable lossless and near-lossless compression of CT and MRI biomedical images | |
| US20030103680A1 (en) | Block boundary artifact reduction for block-based image compression | |
| CN1767655A (en) | Multi view point video image parallax difference estimating method | |
| GB2481612A (en) | Updating image regions in a shared image system | |
| RU2567988C2 (en) | Encoder, method of encoding data, decoder, method of decoding data, system for transmitting data, method of transmitting data and programme product | |
| US20060078050A1 (en) | System and method for increasing SVC compressing ratio | |
| US8958642B2 (en) | Method and device for image processing by image division | |
| CN101710985B (en) | Image brightness compensation method for image coding | |
| CN101742320B (en) | Image processing method | |
| CN100388792C (en) | Image processing method of increasing information encoding-decoding efficiency | |
| CN102186085A (en) | Video processing method, video processing device and system | |
| CN109547784A (en) | A kind of coding, coding/decoding method and device | |
| CN104702959B (en) | A kind of intra-frame prediction method and system of Video coding | |
| CN101765012B (en) | Image information processing method | |
| EP1499114A2 (en) | Noise reduction apparatus | |
| Puthooran et al. | Lossless compression of medical images using a dual level DPCM with context adaptive switching neural network predictor | |
| Alam et al. | An improved JPEG image compression algorithm by modifying luminance quantization table | |
| CN101771877B (en) | Information processing method | |
| US8787686B2 (en) | Image processing device and image processing method | |
| CN110443754B (en) | Method for improving resolution of digital image | |
| Kim et al. | A lossless color image compression method based on a new reversible color transform | |
| JP3759537B2 (en) | Image signal transmission apparatus and image signal transmission method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| DD01 | Delivery of document by public notice |
Addressee: Li Bohang Document name: Notification to Pay the Fees |
|
| DD01 | Delivery of document by public notice |
Addressee: Li Bohang Document name: Notification of Termination of Patent Right |
|
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20120725 Termination date: 20150120 |
|
| EXPY | Termination of patent right or utility model |