Apparatus and methods for recompression of digital images

• US 9,503,738 B2
• Filed: 10/29/2014
• Issued: 11/22/2016
• Est. Priority Date: 10/05/2009
• Status: Active Grant

• Current Assignee: Beamr Imaging Ltd.
• Original Assignee: Beamr Imaging Ltd.
• Inventors: Carmel, Sharon, Gill, Dror, Shoham, Tamar
• Primary Examiner(s): TSAI, TSUNG YIN
• Application Number:
  US14/527,218
• Publication Number:
  US 20150049957A1
• Time in Patent Office: 755 Days
• Field of Search: None
• US Class Current: 1/1
• CPC Class Codes: H04N 19/124 Quantisation
• CPC Class Codes: H04N 19/126 Details of normalisation or weighting functions, e.g. normalisation matrices or variable uniform quantisers
• CPC Class Codes: H04N 19/136 Incoming video signal characteristics or properties
• CPC Class Codes: H04N 19/14 Coding unit complexity, e.g. amount of activity or edge presence estimation H04N19/146 takes precedence
• CPC Class Codes: H04N 19/154 Measured or subjectively estimated visual quality after decoding, e.g. measurement of distortion use of rate-distortion criteria H04N19/147
• CPC Class Codes: H04N 19/17 the unit being an image region, e.g. an object
• CPC Class Codes: H04N 19/176 the region being a block, e.g. a macroblock
• CPC Class Codes: H04N 19/182 the unit being a pixel
• CPC Class Codes: H04N 19/192 the adaptation method, adaptation tool or adaptation type being iterative or recursive
• CPC Class Codes: H04N 19/50 using predictive coding H04N19/61 takes precedence
• CPC Class Codes: H04N 19/60 using transform coding
• CPC Class Codes: H04N 19/625 using discrete cosine transform [DCT]
• CPC Class Codes: H04N 19/86 involving reduction of coding artifacts, e.g. of blockiness

Abstract

A system and method for generating a second reduced size digital image from a first digital image, the method including iteratively compressing the first digital image to an extent determined by a quality measure comprising at least a blockiness measure quantifying added artifactual edges along coding block boundaries of the second image and/or use of a quantization matrix generated by computing a weighted average of the quantization matrix of the first digital image and a scaled second quantization matrix.

Claims

1. A computerized method of enabling an image-adaptive, perceptually-lossless and near-maximal image compression, including:

compressing a first image giving rise to a second image;

implementing a measure of added artifactual edges along coding block boundaries, including;

computing a difference image between the first and second images;

defining a region within said difference image, said region comprising a plurality of coding blocks;

within said region, computing for each boundary between two coding blocks a respective added-blockiness score indicating an extent of added artifactual edges along the respective boundary;

computing a region quality score based on the added-blockiness scores computed for each boundary within the region; and

determining based at least upon said region quality score whether a perceptual quality criterion is met by said second image.

2. The computerized method according to claim 1, wherein said first image is an input image and said second image is a provisionally compressed image, and said compressing is carried out using provisional compression parameters, and wherein one or more further iterations of a search for improved compression parameters is invoked if it is determined that the region quality score for the second image does not meet a perceptual quality criterion.

3. The computerized method according to claim 2, wherein said compressing comprises, at each individual iteration from among said iterations, adapting a compression parameter based on at least one iteration previous to said individual iteration.

4. The computerized method according to claim 3, wherein said compressing comprises, at each individual iteration from among said iterations, adapting a compression parameter based on all iterations previous to said individual iteration.

5. The computerized method according to claim 1 and also comprising providing compression instructions based at least in part on the region quality score.

6. The computerized method according to claim 1 wherein the extent to which said first image is iteratively compressed is also determined by a quality measure other than said added artifactual edges measure.

7. The computerized method according to claim 6 wherein said quality measure comprises a textural measure quantifying textural similarities between the first and second images.

8. The computerized method according to claim 6 wherein said quality measure comprises a local similarity measure quantifying local similarities between the first and second images.

9. The computerized method according to claim 1 wherein said first image comprises a compressed image such that said compressing comprises a process of recompression.

10. The computerized method according to claim 9 wherein said first image comprises a disjoint block level encoded image compressed by independent coding of disjoint blocks in a precursor image.

11. The computerized method according to claim 9 wherein said second image comprises a disjoint block level encoded image generated from said first digital image by independently coding disjoint blocks in the first image.

12. The computerized method according to claim 10 wherein said disjoint block level encoded image comprises a JPEG encoded image.

13. The computerized method according to claim 11 wherein said disjoint block level encoded image comprises a JPEG encoded image.

14. The computerized method according to claim 1 wherein said second image comprises an intra-prediction encoded image.

15. The computerized method according to claim 14 wherein said intra-prediction encoded image comprises an H.264 image.

16. The computerized method according to claim 1 wherein said first image comprises an intra-prediction encoded image.

17. The computerized method according to claim 16 wherein said intra-prediction encoded image comprises an H.264 image.

18. The computerized method according to claim 1 wherein said image compression comprises JPEG coding or H.264 High Profile coding and said coding blocks comprise 8 pixel×

8 pixel blocks.

19. The computerized method according to claim 1 wherein said image compression comprises H.264 coding and said coding blocks comprise 4 pixel×

4 pixel blocks or 16 pixel×

16 pixel blocks.

20. A computerized method comprising iteratively compressing a first digital image into a second reduced size digital image to an extent determined by a plurality of quality measures including a local similarity measure quantifying local similarities between the first image and the second reduced size image and a texture change measure between the first image and the second reduced size image.

21. The computerized method according to claim 20 wherein said extent is determined such that a first texture change between said first and second images is tolerated if the local similarity measure is high whereas only a second texture change between said first and second images, smaller than said first texture change, is tolerated if the local similarity measure is low.

22. The computerized method according to claim 20 wherein said first image comprises a compressed image such that said iterative compressing comprises a process of recompression.

23. The computerized method according to claim 22 wherein said texture measure comprises a quantitative measure of changes in texture of corresponding areas between the first and second digital images.

24. The computerized method according to claim 23 wherein said compression comprises H.264 coding and said areas comprise 4 pixel×

4 pixel blocks or 16 pixel×

16 pixel blocks.

25. The computerized method according to claim 23 wherein said compression comprises JPEG coding or H.264 High Profile coding and said coding blocks comprise 8 pixel×

8 pixel blocks.

27. The computerized method according to claim 20 wherein said plurality of quality measures are mutually normalized and said extent depends on a product.

28. The computerized method according to claim 20 wherein said plurality of quality measures are mutually normalized and said extent depends on a weighted geometric mean of said mutually normalized plurality of quality measures.

29. The computerized method according to claim 20 and wherein said iteratively compressing includes a plurality of iterations.

30. The computerized method according to claim 22 and wherein said iteratively compressing includes a plurality of iterations.

26. A computerized method that iteratively compresses a first digital image into a second reduced size digital image to an extent determined by a texture change measure including:

performing at least one initial compression using at least one initial compression parameter,

evaluating said initial compression by computing a textural change measure between the first digital image and the second reduced size digital image;

determining whether the texture change measure falls within a textural change measure interval; and

if said textural change measure falls within the textural change measure interval, terminating the method, and otherwise, compressing further using a further compression parameter larger or smaller than said initial compression parameter if said textural change measure falls on one or another side of the textural change measure interval respectively.

31. The computerized method according to claim 26 and wherein said iteratively compressing includes a plurality of iterations.

32. A system for enabling an image-adaptive, perceptually-lossless and near-maximal image compression, the system having a processor configured to:

compress a first image giving rise to a second image;

implement a measure of added artifactual edges along coding block boundaries, including;

compute a difference image between the first and second images;

defining a region within said difference image, said region comprising a plurality of coding blocks;

within said region, compute for each boundary between two coding blocks a respective added-blockiness score indicating an extent of added artifactual edges along the respective boundary;

compute a region quality score based on the added-blockiness scores computed for each boundary within the region; and

determine based at least upon said region quality score whether a perceptual quality criterion is met by said second image.

33. A system having a processor configured to iteratively compress a first digital image into a second reduced size digital image to an extent determined by a plurality of quality measures including a local similarity measure quantifying local similarities between the first image and the second reduced size image and a texture change measure between the first image and the second reduced size image.

34. A system for iteratively compressing a first digital image into a second reduced size digital image to an extent determined by a texture change measure, the system having a processor configured to:

perform at least one initial compression using at least one initial compression parameter;

evaluate said initial compression by computing a textural change measure between the first digital image and the second reduced size digital image;

determine whether the texture change measure falls within a textural change measure interval; and

if said textural change measure falls within the textural change measure interval, terminate the method, and otherwise, compress further using a further compression parameter larger or smaller than said initial compression parameter if said textural change measure falls on one or another side of the textural change measure interval respectively.

35. A non-transitory computer usable medium having a computer readable program code embodied therein, said computer readable program code adapted to be executed to perform a method of enabling an image-adaptive, perceptually-lossless and near-maximal image compression, including:

compressing a first image giving rise to a second image;

implementing a measure of added artifactual edges along coding block boundaries, including;

computing a difference image between the first and second images;

defining a region within said difference image, said region comprising a plurality of coding blocks;

within said region, computing for each boundary between two coding blocks a respective added-blockiness score indicating an extent of added artifactual edges along the respective boundary;

computing a region quality score based on the added-blockiness scores computed for each boundary within the region; and

determining based at least upon said region quality score whether a perceptual quality criterion is met by said second image.

36. A non-transitory computer usable medium having a computer readable program code embodied therein, said computer readable program code adapted to be executed to perform a method comprising:

iteratively compressing a first digital image into a second reduced size digital image to an extent determined by a plurality of quality measures including a local similarity measure quantifying local similarities between the first image and the second reduced size image and a texture change measure between the first image and the second reduced size image.

37. A non-transitory computer usable medium having a computer readable program code embodied therein, said computer readable program code adapted to be executed to perform a method of iteratively compressing a first digital image into a second reduced size digital image to an extent determined by a texture change measure, including:

performing at least one initial compression using at least one initial compression parameter,

evaluating said initial compression by computing a textural change measure between the first digital image and the second reduced size digital image;

determining whether the texture change measure falls within a textural change measure interval; and

if said textural change measure falls within the textural change measure interval, terminating the method, and otherwise, compressing further using a further compression parameter larger or smaller than said initial compression parameter if said textural change measure falls on one or another side of the textural change measure interval respectively.