Preserving Perceptual Contrast in Decolorization with Optimized Color Orders

Converting a color image to a grayscale image, namely decolorization, is an important process for many real-world applications. Previous methods build contrast loss functions to minimize the contrast differences between the color images and the resultant grayscale images. In this paper, we improve upon a widely used decolorization method with two extensions. First, we relax the need for heuristics on color orders, which the baseline method relies on when computing the contrast differences. In our method, the color orders are incorporated into the loss function and are determined through optimization. Moreover, we apply a nonlinear function on the grayscale contrast to better model human perception of contrast. Both qualitative and quantitative results on the standard benchmark demonstrate the effectiveness of our two extensions.


Presented at:
IEEE International Conference on Image Processing (ICIP), Beijing, China, September 17-20, 2017
Year:
2017
Laboratories:




 Record created 2017-10-12, last modified 2018-09-13

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