Automatic contrast enhancement

• US 7,319,787 B2
• Filed: 11/29/2004
• Issued: 01/15/2008
• Est. Priority Date: 07/06/2001
• Status: Expired due to Fees

• Current Assignee: Intel Corporation
• Original Assignee: Corel Corporation (Corel Holdings LP)
• Inventors: Zaklika, Kryzstof Antoni, Trifonov, Mikhail Ivanovich, Sharonova, Olga Vadimovna
• Primary Examiner(s): Alavi; Amir
• Application Number:
  US10/998,436
• Publication Number:
  US 20050100242A1
• Time in Patent Office: 1,142 Days
• Field of Search: 382/162, 382/168, 382/169, 382/170, 382/172, 382/254, 382/270, 382/274, 382/276, 382/277, 382/286, 358/447, 358/509, 358/518, 358/519, 358/520, 358/522, 348/672, 348/678, 345/589, 345/590, 345/600
• US Class Current: 382/168
• CPC Class Codes: G06T 5/40 using histogram techniques
• CPC Class Codes: G06T 5/92 based on global image properties

Abstract

A method of automatic contrast correction comprises providing digital image data, representing the data in the form of a brightness histogram, determining a measure of central tendency for said histogram, adding a shift value to the measure of central tendency to provide an adjusted measure of central tendency, using the both the determined and adjusted measures of central tendency to determine the exponent of a tone reproduction curve, and applying the tone reproduction curve to the brightness values of the image. Additionally, the method may provide further correction by applying to the brightness values of the image an S-shaped tone reproduction curve that does not change a measure of central tendency of the brightness histogram.

Claims

1. A computer-readable medium storing computer-executable instructions for performing a computer process for automatic contrast correction, the computer process comprising:

providing digital image data;

representing the data in the form of a brightness histogram;

determining a measure of central tendency for said histogram as a determined measure of central tendency;

adding a shift value to the measure of central tendency to provide an adjusted measure of central tendency;

computing a tone reproduction curve by a ratio containing logarithms of determined and adjusted measures of central tendency;

and applying this tone reproduction curve to brightness values of the image.

2. The computer-readable medium of claim 1 wherein the shift value is zero for a mean brightness of zero and increases to a maximum with increasing mean brightness before falling to zero at an intermediate mean brightness, and as mean brightness increases beyond the intermediate mean brightness, the shift value decreases, falling to a negative minimum value before increasing to zero again at the maximum mean brightness that the image can have.

4. The computer-readable medium of claim 1 wherein there is also applied an S-shaped tone reproduction curve that does not change a measure of central tendency of the brightness histogram.

3. The computer-readable medium of claimi wherein the tone reproduction curve is given by

L′

_i=N(L_i/N)^1/γ

where L_i is any original brightness value L′

_i a corresponding enhanced brightness value, N is the largest possible brightness value, and γ

is an exponent.

5. A computer-readable medium storing computer-executable instructions for performing a computer process for contrast correction, the computer process comprising:

providing digital image data;

representing the data in the form of a brightness histogram;

determining a measure of central tendency for said histogram; and

applying to brightness values of the image an S-shaped tone reproduction curve that does not change a measure of central tendency of the brightness histogram.

6. The computer-readable medium of claim 5 wherein the computer process further comprises:

integrating the brightness histogram to generate an integral histogram, wherein the S-shaped tone reproduction curve is generated by linear region fitting to at least a portion of the integral histogram.

7. The computer-readable medium of claim 5 wherein the computer process further comprises:

integrating the brightness histogram to generate an integral histogram, wherein the S-shaped tone reproduction curve is chosen from a set of curves according to brightness values corresponding to lower and upper values of the integral histogram.

8. A computer-readable medium storing computer-executable instructions for performing a computer process for automatic contrast correction, the computer process comprising:

providing digital image data;

representing the data in the form of a brightness histogram;

determining a measure of central tendency for said histogram; and

applying to brightness values of the image an S-shaped tone reproduction curve that does not change a measure of central tendency of the brightness histogram, wherein the shape of the S-shaped tone reproduction curve is determined by linear regression on the integral brightness histogram.

9. computer-readable medium storing computer-executable instructions for performing a computer process for correcting contrast in a digital image, the computer process comprising:

determining a histogram of brightness values in the digital image;

determining a measure of central tendency of the histogram;

computing a shift value as a function of the measure of central tendency of the histogram;

applying the shift value to the measure of central tendency to generate a measure of adjusted central tendency;

generating a non-linear transformation based on the measures of central tendency and adjusted central tendency; and

applying the non-linear transformation to the brightness values in the digital image to correct contrast in the digital image.

10. The computer-readable medium of claim 9 wherein the operation of generating a non-linear transformation comprises:

computing an exponent of a tone reproduction curve to generate the non-linear transformation.

11. The computer-readable medium of claim 9 wherein the operation of generating a non-linear transformation comprises:

generating an S-shaped tone reproduction curve as the non-linear transformation.

12. The computer-readable medium of claim 11 wherein the computer process further comprises:

integrating the brightness histogram to generate an integral histogram, wherein the S-shaped tone reproduction curve is generated by linear region fitting to at least a portion of the integral histogram.

13. The computer-readable medium of claim 11 wherein the computer process further comprises:

integrating the brightness histogram to generate an integral histogram, wherein the S-shaped tone reproduction curve is chosen from a set of curves according to brightness values corresponding to lower and upper values of the integral histogram.

14. The computer-readable medium of claim 9 wherein the operation of generating a non-linear transformation is given by

L′

_i=N(L_i/N)^1/γ

where L′

_i is any original brightness value, L′

_i a corresponding enhanced brightness value, N is the largest possible brightness value, and γ

is an exponent based on the measures of central tendency and adjusted central tendency.

15. The computer readable medium of claim 9 wherein the operation of applying the non-linear transformation to the brightness values in the digital image to correct contrast in the digital image shifts a measure of central tendency of the transformed brightness values from the measure of central tendency of the histogram.

16. The computer readable medium of claim 9 wherein the operation of applying the non-linear transformation to the brightness values in the digital image to correct contrast in the digital image does not shift a measure of central tendency of the transformed brightness values from the measure of central tendency of the histogram.

17. A method of correcting contrast in a digital image, the method comprising:

determining a histogram of brightness values in the digital image;

determining a measure of central tendency of the histogram;

computing a shift value as a function of the measure of central tendency of the histogram;

applying the shift value to the measure of central tendency to generate a measure of adjusted central tendency;

generating a non-linear transformation based on the measures of central tendency and adjusted central tendency; and

applying the non-linear transformation to the brightness values in the digital image to correct contrast in the digital image.

18. The method of claim 17 wherein the operation of generating a non-linear transformation comprises:

computing an exponent of a tone reproduction curve to generate the non-linear transformation.

19. The method of claim 17 wherein the operation of generating a non-linear transformation comprises:

generating an S-shaped tone reproduction curve as the non-linear transformation.

20. The method of claim 19 further comprising:

integrating the brightness histogram to generate an integral histogram, wherein the S-shaped tone reproduction curve is generated by linear region fitting to at least a portion of the integral histogram.

21. The method of claim 19 further comprising:

integrating the brightness histogram to generate an integral histogram, wherein the S-shaped tone reproduction curve is chosen from a set of curves according to brightness values corresponding to lower and upper values of the integral histogram.

22. The method of claim 17 wherein the operation of generating a non-linear transformation is given by

L′

_i=N(L_i/N)^1/γ

where L_i is any original brightness value, L′

_i a corresponding enhanced brightness value, N is the largest possible brightness value, and γ

is an exponent based on the measures of central tendency and adjusted central tendency.

23. The method of claim 17 wherein the operation of applying the non-linear transformation to the brightness values in the digital image to correct contrast in the digital image shifts a measure of central tendency of the transformed brightness values from the measure of central tendency of the histogram.

24. The method of claim 17 wherein the operation of applying the non-linear transformation to the brightness values in the digital image to correct contrast in the digital image does not shift a measure of central tendency of the transformed brightness values from the measure of central tendency of the histogram.