Naturalness- and information-preserving image recoloring for red–green dichromats

• Published in: Signal processing. Image communication Vol. 76; pp. 68 - 80
• Main Authors: Zhu, Zhenyang, Toyoura, Masahiro, Go, Kentaro, Fujishiro, Issei, Kashiwagi, Kenji, Mao, Xiaoyang
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01.08.2019; Elsevier BV
• Subjects: Algorithms; Color vision; Computer simulation; Contrast; Naturalness; Optimization; Quantitative analysis; Red–green dichromat; Shortages; Naturalness; Contrast; Red–green dichromat; Optimization
• ISSN: 0923-5965; 1879-2677
• DOI: 10.1016/j.image.2019.04.004

More than 100 million individuals around the world suffer from color vision deficiency (CVD). Image recoloring algorithms have been proposed to compensate for CVD. This study has proposed a new recoloring algorithm to make up shortages of contrast enhancement and naturalness preservation of the state-of-the-art methods. The recoloring task is formulated as an optimization problem that is solved by using the colors in a simulated CVD color space to maximize contrast and to preserve the original color as much as possible. In addition, the dominant colors are extracted for recoloring. They are then propagated to the whole image so that the optimization problem could be solved at a reasonable cost independent of the image size. In the quantitative evaluation, the results of the proposed method are competitive with those of the best existing method. The evaluation involving subjects with CVD demonstrates that the proposed method outperforms the state-of-the-art method in preserving both the information and the naturalness of images. •Propose an optimization based recoloring model for red–green dichromats compensation.•Enhance global and local contrast and maintain dichromats identifiable information.•Provide a more stable implementation for solving the recoloring problem.