CONTENT ADAPTIVE HISTOGRAM ENHANCEMENT

• US 20100080459A1
• Filed: 09/26/2008
• Published: 04/01/2010
• Est. Priority Date: 09/26/2008
• Status: Abandoned Application

• Current Assignee: Qualcomm, Inc.
• Original Assignee: Qualcomm, Inc.
• Inventors: Lai, King-Chuang, Dai, Min, Teng, Chia-Yuan
• Application Number:
  US12/238,775
• Publication Number:
  US 20100080459A1
• Time in Patent Office: Days
• US Class Current: 382/170
• CPC Class Codes: G06T 2207/10016 Video; Image sequence
• CPC Class Codes: G06T 5/40 using histogram techniques
• CPC Class Codes: G06T 5/92 based on global image properties

Abstract

This disclosure describes techniques for performing content adaptive histogram enhancement. In accordance with the content adaptive histogram enhancement techniques of this disclosure, a frame of digital image data, e.g., digital video data or digital still image data, is classified into one of a plurality of content classes based on histogram of pixel intensity values of the frame. The content classes may represent various levels of brightness, contrast, or the like. To classify the frame into the corresponding content class, a shape of the histogram may be analyzed using various histogram statistics. Based on the content class of the frame, the pixel intensity values of the frame are mapped to new pixel intensity values.

Claims

1. A method for processing digital image data comprising:

analyzing a distribution of pixel intensity values of a frame of the digital image data to classify the frame into one of a plurality of content classes; and

adjusting the pixel intensity values of the frame based on the classification of the frame.

2. The method of claim 1, wherein analyzing the distribution of pixel intensity values of the frame comprises:

generating a histogram of the pixel intensity values of the frame; and

analyzing a shape of the histogram to classify the frame into one of the plurality of content classes.

3. The method of claim 1, wherein analyzing the shape of the histogram comprises analyzing at least one of a mean pixel intensity value of the histogram, a location of one or more peaks of the histogram, and a width of one or more peaks of the histogram to classify the frame into one of the plurality of content classes.

4. The method of claim 1, wherein the frame comprises a first frame, the method further comprising:

comparing a distribution of pixel intensity values of a second frame of digital image data to the distribution of pixel intensity values of the first frame; and

adjusting the pixel intensity values of the first frame based on a content class of the second frame when the comparison indicates the first and second frame are substantially similar.

5. The method of claim 1, wherein adjusting the pixel intensity values of the frame based on the classification of the frame comprises:

maintaining a plurality of pixel mapping look up tables (LUTs), wherein each of the pixel mapping LUTs corresponds with one of the content classes;

selecting one of the plurality of pixel mapping LUTs based on the content class to which the frame is classified; and

mapping the pixel intensity values of the frame to new pixel intensity values using the selected one of the plurality of LUTs.

6. The method of claim 5, further comprising generating the plurality of LUTs using a pixel mapping function that is adaptive based on the content class to which the frame is classified.

7. The method of claim 1, wherein the pixel intensity values represent luminance (Y) pixel values, the method further comprising adjusting pixel color values representing chrominance values of the frame by multiplying the pixel color values of the frame by a factor.

8. The method of claim 7, wherein the factor used in adjusting the pixel color values of the frame is a ratio between of an integration from 0 to a of a pixel mapping function ƒ

(x) used to adjust the pixel intensity values and an integration from 0 to a of function y=x, where a is a chop point.

9. The method of claim 1, wherein each of the plurality of content classes correspond with a level of brightness, a level of contrast or both within the frame.

10. The method of claim 1, wherein the frame of digital image data comprises a frame of a sequence of digital video data.

11. A device for processing digital image data comprising:

a frame classification unit that analyzes a distribution of pixel intensity values of a frame of the digital image data to classify the frame into one of a plurality of content classes; and

pixel mapping unit to adjust the pixel intensity values of the frame based on the classification of the frame.

12. The device of claim 11, wherein the frame classification unit generates a histogram of the pixel intensity values of the frame and analyzes a shape of the histogram to classify the frame into one of the plurality of content classes.

13. The device of claim 11, wherein the frame classification unit analyzes at least one of a mean pixel intensity value of the histogram, a location of one or more peaks of the histogram, and a width of the one or more peaks of the histogram to classify the frame into one of the plurality of content classes.

14. The device of claim 11, wherein the frame comprises a first frame and the frame classification unit compares a distribution of pixel intensity values of a second frame of digital image data to the distribution of pixel intensity values of the first frame and adjusts the pixel intensity values of the first frame based on a content class of the second frame when the comparison indicates the first and second frame are substantially similar.

15. The device of claim 14, wherein the frame classification unit adjusts the pixel intensity values of the first frame based on a combination of a look-up table corresponding with the content class of the first frame and a look-up table corresponding with the content class of the second frame, wherein the look-up tables of the content class of the first frame and the content class of the second frame are combined as a function of an alpha blending function, where alpha is between zero and one.

16. The device of claim 11, further comprising:

a look-up table (LUT) generation unit that maintains a plurality of pixel mapping look-up tables (LUTs), each of the pixel mapping LUTs corresponding with one of the content classes;

wherein the pixel mapping unit selects one of the plurality of pixel mapping LUTs based on the content class to which the frame is classified and maps the pixel intensity values of the frame to new pixel intensity values using the selected one of the plurality of LUTs.

17. The device of claim 16, wherein the LUT generation unit generates the plurality of LUTs using a pixel mapping function that is adaptive based on the content class to which the frame is classified.

18. The device of claim 11, wherein the pixel intensity values represent luminance (Y) pixel values and the pixel mapping unit adjusts pixel color values representing chrominance values of the frame by multiplying the pixel color values of the frame by a factor.

19. The device of claim 18, wherein the factor used in adjusting the pixel color values of the frame is a ratio between of an integration from 0 to a of a pixel mapping function ƒ

(x) used to adjust the pixel intensity values and an integration from 0 to a of function y=x, where a is a chop point.

20. The device of claim 11, wherein each of the plurality of content classes correspond with a level of brightness, a level of contrast or both within the frame.

21. The device of claim 11, wherein the frame of digital image data comprises a frame of a sequence of digital video data.

22. The device of claim 11, wherein the device comprises a wireless communication device.

23. The device of claim 11, wherein the device comprises an integrated circuit device.

33. The computer-readable medium of claim 23, wherein the frame of digital image data comprises a frame of a sequence of digital video data.

24. A computer-readable medium for processing digital image data comprising instructions that when executed cause at least one processor to:

analyze a distribution of pixel intensity values of a frame of the digital image data to classify the frame into one of a plurality of content classes; and

adjust the pixel intensity values of the frame based on the classification of the frame.

25. The computer-readable medium of claim 24, wherein the instructions that cause the at least one processor to analyze the distribution of pixel intensity values of the frame comprise instructions to cause the at least one processor to:

generate a histogram of the pixel intensity values of the frame; and

analyze a shape of the histogram to classify the frame into one of the plurality of content classes.

26. The computer-readable medium of claim 24, wherein the instructions that cause the at least one processor to analyze the shape of the histogram comprise instructions that cause the at least one processor to analyze at least one of a mean pixel intensity value of the histogram, a location of one or more peaks of the histogram, and a width of one or more peaks of the histogram to classify the frame into one of the plurality of content classes.

27. The computer-readable medium of claim 24, wherein the frame comprises a first frame, the computer-readable medium further comprising instructions that cause the at least one processor to:

compare a distribution of pixel intensity values of a second frame of digital image data to the distribution of pixel intensity values of the first frame; and

adjust the pixel intensity values of the first frame based on a content class of the second frame when the comparison indicates the first and second frame are substantially similar.

28. The computer-readable medium of claim 24, wherein the instructions that cause the at least one processor to adjust the pixel intensity values of the frame based on the classification of the frame comprise instructions that cause the at least one processor to:

maintain a plurality of pixel mapping look up tables (LUTs), wherein each of the pixel mapping LUTs corresponds with one of the content classes;

select one of the plurality of pixel mapping LUTs based on the content class to which the frame is classified; and

map the pixel intensity values of the frame to new pixel intensity values using the selected one of the plurality of LUTs.

29. The computer-readable medium of claim 28, further comprising instructions that cause the at least one processor to generate the plurality of LUTs using a pixel mapping function that is adaptive based on the content class to which the frame is classified.

30. The computer-readable medium of claim 24, wherein the pixel intensity values represent luminance (Y) pixel values, the computer-readable medium further comprising instructions that cause the at least one processor to adjust pixel color values representing chrominance values of the frame by multiplying the pixel color values of the frame by a factor.

31. The computer-readable medium of claim 30, wherein the factor used in adjusting the pixel color values of the frame is a ratio between of an integration from 0 to a of a pixel mapping function ƒ

(x) used to adjust the pixel intensity values and an integration from 0 to a of function y=x, where a is a chop point.

32. The computer-readable medium of claim 24, wherein each of the plurality of content classes correspond with a level of brightness, a level of contrast or both within the frame.

34. A device for processing digital image data comprising:

means for analyzing a distribution of pixel intensity values of a frame of the digital image data to classify the frame into one of a plurality of content classes; and

means for adjusting the pixel intensity values of the frame based on the classification of the frame.

35. The device of claim 34, wherein the analyzing means generate a histogram of the pixel intensity values of the frame and analyze a shape of the histogram to classify the frame into one of the plurality of content classes.

36. The device of claim 34, wherein the analyzing means analyze at least one of a mean pixel intensity value of the histogram, a location of one or more peaks of the histogram, and a width of one or more peaks of the histogram to classify the frame into one of the plurality of content classes.

37. The device of claim 34, wherein the frame comprises a first frame, the device further comprising:

means for comparing a distribution of pixel intensity values of a second frame of digital image data to the distribution of pixel intensity values of the first frame; and

the means for adjusting adjusts the pixel intensity values of the first frame based on a content class of the second frame when the comparison indicates the first and second frame are substantially similar.

38. The device of claim 34, further comprising:

means for maintaining a plurality of pixel mapping look up tables (LUTs), wherein each of the pixel mapping LUTs corresponds with one of the content classes; and

means for selecting one of the plurality of pixel mapping LUTs based on the content class to which the frame is classified;

wherein the adjusting means maps the pixel intensity values of the frame to new pixel intensity values using the selected one of the plurality of LUTs.

39. The device of claim 38, further comprising means for generating the plurality of LUTs using a pixel mapping function that is adaptive based on the content class to which the frame is classified.

40. The device of claim 34, wherein the pixel intensity values represent luminance (Y) pixel values and the adjusting means adjusts pixel color values representing chrominance values of the frame by multiplying the pixel color values of the frame by a factor.

41. The device of claim 40, wherein the factor used in adjusting the pixel color values of the frame is a ratio between of an integration from 0 to a of a pixel mapping function ƒ

(x) used to adjust the pixel intensity values and an integration from 0 to a of function y=x, where a is a chop point.

42. The device of claim 34, wherein each of the plurality of content classes correspond with a level of brightness, a level of contrast or both within the frame.

43. The device of claim 34, wherein the frame of digital image data comprises a frame of a sequence of digital video data.