Rendering of high dynamic range images

1. A method for processing high dynamic range image data which includes pixels whose values have a high dynamic range, so as to obtain counterpart image data which is renderable, the method comprising:

using computer to perform the following steps:

classifying each pixel of the high dynamic range image data into one of at least two different portions which include a relatively lighter portion and a relatively darker portion;

identifying an image adaptation point for each of said different portions, said identifying step including the steps of identifying a first image adaptation point for the lighter portion and identifying a second image adaptation point for the darker portion; and

performing white point adjustment for the value of each pixel in each of said different portions by using the corresponding image adaptation point for each said portion, said step of performing white point adjustment including the steps of performing a first white point adjustment for the values of pixels of the lighter portion using the first image adaptation point and performing a second white point adjustment for the values of the pixels of the darker portion using the second image adaptation point.

2. The method of claim 1 , further comprising determining the relatively lighter portion and the relatively darker portion using a threshold value.

3. The method of claim 2 , wherein the threshold value is measured in luminance, wherein the relatively lighter portion includes an area of the image having a luminance value greater than the threshold value, and the relatively darker portion includes an area of the image having a luminance value less tart or equal to the threshold value.

4. The method of claim 3 , further comprising determining the threshold value by:

calculating a cumulative histogram of luminance of the image; and

equating the threshold value to a luminance value at a point of minimal slope of the histogram.

5. The method of claim 3 , further comprising determining the threshold value by:

determining an ISODATA threshold of the image; and

equating the threshold value to the ISODATA threshold.

6. The method of claim 1 , wherein the first white point adjustment is based on a first grey world assumption for the relatively lighter portion using the first image adaptation point, and the second white point adjustment is based on a second grey world assumption for the relatively darker portion using the second image adaptation point.

7. The method of claim 1 , wherein the first white point adjustment is based on a first perfect reflecting diffuser assumption for the relatively lighter portion using the first image adaptation point, and the second white point adjustment is based on a second perfect reflecting diffuser assumption for the relatively darker portion using the second image adaptation point.

8. The method of claim 1 , wherein:

the first white point adjustment is based on a first ratio of a first grey world assumption to a first perfect reflecting diffuser assumption;

the second white point adjustment is based on a second ratio of a second grey world assumption to a second perfect reflecting diffuser assumption; and

the first grey world assumption and the first perfect reflecting diffuser assumption are determined for the relatively lighter portion and based on the first image adaptation point, and the second grey world assumption and the second perfect reflecting diffuser assumption are determined for the relatively darker portion and based on the second image adaptation point.

9. The method of claim 1 , further comprising:

normalizing the image so that an image minimum value equals zero, an image maximum value equals one, and an image mean value equals 0.5.

10. The method of claim 9 , further comprising:

converting the normalized image to an HSV image in HSV format;

performing at least one saturation boost and a sharpness enhancement on the HSV image to obtain a new HSV image; and

converting the new HSV image to an RGB image in RGB format.

11. The method of claim 10 , further comprising:

calculating a cumulative histogram of luminance of the new HSV image; and

equating a threshold value to a luminance value at a point of minimal slope of the histogram.

12. The method of claim 11 , wherein the relatively lighter portion includes a portion of the RGB image having a luminance value greater than the threshold value, and the relatively darker portion includes a portion of the RGB image having a luminance value less than or equal to the threshold value.

13. The method of claim 12 , wherein a user selects the level of saturation boost.

14. The method of claim 1 , wherein the first and second adaptation points are identified using an identifying process, and the identifying process is selected from the group consisting of the grey world assumption and the point of highest luminance.

15. The method of claim 1 , further comprising rendering the image subsequent to the first white point adjustment and the second white point adjustment.

16. The method of claim 15 , wherein rendering further includes applying an image-dependent gamma correction, a saturation adjustment, and a sharpening filter.

17. An apparatus for processing high dynamic range image data which includes pixels whose values have a high dynamic range, so as to obtain counterpart image data which is renderable, the apparatus comprising:

classifying means for classifying each pixel of the high dynamic range image data into one of two different portions which include a relatively lighter portion and a relatively darker portion;

an identification means for identifying an image adaptation point for each of said different portions, said identification means including means for identifying a first image adaptation point for the lighter portion and for identifying a second image adaptation point for the darker portion; and

a white point adjustment means for performing white point adjustment for the value of each pixel in each of said different portions by using the corresponding image adaptation point for each said portion, said white point adjustment means including means for performing a first white point adjustment for the values of the pixels of the lighter portion using the first image adaptation point and for performing a second white point adjustment for the values of the pixels of the darker portion using the second image adaptation point.

18. A computer-readable medium that stores computer-executable process steps, said computer-executable process steps for performing white balance normalization of a high dynamic range image, the computer-executable instructions executable to perform a method according to any of claims 1 to 16 .

19. An apparatus for processing high dynamic range image data which includes pixels whose values have a high dynamic range, so as to obtain counterpart image data which is renderable, the apparatus comprising:

a classifying unit adapted to classify each pixel of the high dynamic range image data into one of at least two different portions which include a relatively lighter portion and a relatively darker portion;

an identifying unit adapted to identify an image adaptation point for each of said different portions, said identifying step including the steps of identifying a first image adaptation point for the lighter portion and identifying a second image adaptation point for the darker portion; and

a performing unit adapted to perform white point adjustment for the value of each pixel in each of said different portions by using the corresponding image adaptation point for each said portion, wherein said performing unit performs white point adjustment including the steps of performing a first white point adjustment for the values of the pixels of the lighter portion using the first image adaptation point and performs a second white point adjustment for the values of the pixels of the darker portion using the second image adaptation point.