Contrast optimization and local adaptation approach for high dynamic range compression
An apparatus is described herein. The apparatus comprises a controller, a logarithmic tone-reproduction operator, a processor, and a compressor. The controller is to calculate a regularization term and a contrast preservation term of an objective function. The logarithmic tone-reproduction operator is to produce a reference image. The processor is to obtain a compressed luminance from the objective function as applied to the reference image. The compressor is to compress a high dynamic range (HDR) image by applying a gain term to the HDR image based on the compressed luminance.
1. An apparatus for contrast optimization and local adaptation for HDR compression of an HDR image, comprising:
a controller to calculate a regularization term and a contrast preservation term of an objective function;
a logarithmic tone-reproduction operator to produce a reference image;
a processor to obtain a compressed luminance from the objective function as applied to the reference image; and
a compressor to compress the HDR image by applying a gain term at least partially based on the compressed luminance to the HDR image.
2. The apparatus of claim 1 , wherein the compressor is to divide a luminance Y HDR by the compressed luminance Y LDR to determine the gain term.
3. The apparatus of claim 1 , wherein the processor is to implement an iterated conditional mode to obtain the compressed luminance.
4. The apparatus of claim 1 , wherein the controller is to modify a regularization parameter of the regularization term to introduce additional information to the objective function.
5. The apparatus of claim 1 , wherein the regularization term comprises a regularization parameter that increases as a likelihood that a neighborhood of the reference image contains a strong edge increases.
6. The apparatus of claim 1 , wherein the contrast preservation term comprises a weighting factor to determine significant contrast ratios of a current neighborhood of pixels.
7. The apparatus of claim 1 , wherein the contrast preservation term is to maintain relative ratios of luminance between neighboring pixels.
8. The apparatus of claim 1 , wherein the logarithmic tone-reproduction operator is to calculate the reference image by compressing an input image.
9. The apparatus of claim 1 , wherein the compressed luminance is obtained via an iterative solution of the objective function.
10. The apparatus of claim 1 , wherein optimization parameters are applied to the logarithmic tone-reproduction operator and the objective function.
11. A method, comprising:
calculating, via a processor, a regularization term and a contrast preservation term of an objective function;
producing a reference image;
obtaining a compressed luminance from the objective function as applied to the reference image; and
compressing an HDR image by applying a gain term to the HDR image at least partially based on the compressed luminance.
12. The method of claim 11 , wherein a luminance Y HDR is divided by the compressed luminance Y LDR to determine the gain term.
13. The method of claim 11 , wherein the compressed luminance is obtained via an iterated conditional mode.
14. The method of claim 11 , wherein the regularization term comprises a regularization parameter to introduce additional information to the objective function to solve the objective function.
15. The method of claim 11 , wherein the regularization term comprises a regularization parameter that increases as a likelihood that a neighborhood of the reference image contains a strong edge increases.
16. The method of claim 11 , wherein the contrast preservation term comprises a weighting factor to determine significant contrast ratios of a current neighborhood of pixels.
17. The method of claim 11 , wherein the contrast preservation term is to maintain relative ratios of luminance between neighboring pixels.
18. The method of claim 11 , wherein a logarithmic tone-reproduction operator is to produce the reference image by compressing an input image.
19. The method of claim 11 , wherein the compressed luminance is obtained via an iterative solution of the objective function.
20. The method of claim 11 , wherein optimization parameters are applied to a logarithmic tone-reproduction operator and the objective function.
21. At least one non-transitory machine-readable medium having instructions stored therein that, in response to being executed on a computing device, cause the computing device to:
calculate, via a processor, a regularization term and a contrast preservation term of an objective function;
produce a reference image;
obtain a compressed luminance from the objective function as applied to the reference image; and
compress a high dynamic range (HDR) image by applying a gain term at least partially based on the compressed luminance to the HDR image.
22. The machine-readable medium of claim 21 , wherein a luminance Y HDR is divided by the compressed luminance Y LDR to determine the gain term.
23. The machine-readable medium of claim 21 , wherein the compressed luminance is obtained via an iterated conditional mode.
24. The machine-readable medium of claim 21 , the regularization term comprises a regularization parameter to introduce additional information to the objective function to solve the objective function.
25. The machine-readable medium of claim 21 , wherein the regularization term comprises a regularization parameter that increases as a likelihood that a neighborhood of the reference image contains a strong edge increases.