Image Decolorization by Maximally Preserving Color Contrast

Author: Alex Yong-Sang Chia, Keita Yaegashi and Soh Masuko


We propose a method to convert a color image to its gray representation with the objective that color contrast in the color image is maximally preserved as gray contrast in the gray image. Given a color image, we first extract unique colors of the image through robust clustering for its color values. Based on the color contrast between these unique colors, we tailor a non-linear decolorization function that maximally preserves contrast in the gray image. A novelty here is the proposal of a color-gray feature that tightly couple color contrast with gray contrast information. We compute the optimal color-gray feature, and drive the search for a decolorization function that generates a color-gray feature that is most similar to the optimal one. This function is then used to convert a color image to its gray representation. Our experiments and user study demonstrate the greater effectiveness of this method in comparison to previous techniques.

Keywords: Image Decolorization, Feature Representation.

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Research Areas : #Vision Program
Careers : Open Positions