학술논문

Personalized Image Recoloring for Color Vision Deficiency Compensation
Document Type
Periodical
Source
IEEE Transactions on Multimedia IEEE Trans. Multimedia Multimedia, IEEE Transactions on. 24:1721-1734 2022
Subject
Components, Circuits, Devices and Systems
Communication, Networking and Broadcast Technologies
Computing and Processing
General Topics for Engineers
Image color analysis
Sensitivity
Optimization
Computational modeling
Clustering algorithms
Adaptation models
Visualization
color vision deficiency
recoloring personalization
contrast enhancement
naturalness preservation
Language
ISSN
1520-9210
1941-0077
Abstract
Several image recoloring methods have been proposed to compensate for the loss of contrast caused by color vision deficiency (CVD). However, these methods only work for dichromacy (a case in which one of the three types of cone cells loses its function completely), while the majority of CVD is anomalous trichromacy (another case in which one of the three types of cone cells partially loses its function). In this paper, a novel degree-adaptable recoloring algorithm is presented, which recolors images by minimizing an objective function constrained by contrast enhancement and naturalness preservation. To assess the effectiveness of the proposed method, a quantitative evaluation using common metrics and subjective studies involving 14 volunteers with varying degrees of CVD are conducted. The results of the evaluation experiment show that the proposed personalized recoloring method outperforms the state-of-the-art methods, achieving desirable contrast enhancement adapted to different degrees of CVD while preserving naturalness as much as possible.