Abstract
Color vision deficiency (CVD) is caused by anomalies in the cone cells of the human retina. It affects approximately 200 million individuals throughout the world. Although previous studies have proposed compensation methods, contrast and naturalness preservation have not been adequately and simultaneously addressed in the state-of-the-art studies. This paper focuses on red–green dichromats’ compensation and proposes a recoloring algorithm that combines contrast enhancement and naturalness preservation in a unified optimization model. In this implementation, representative color extraction and edit propagation methods are introduced to maintain global and local information in the recolored image. The quantitative evaluation results showed that the proposed method is competitive with state-of-the-art methods. A subjective experiment was also conducted and the evaluation results revealed that the proposed method obtained the best scores in preserving both naturalness and information for individuals with severe red–green CVD.
Highlights
The human retina contains two kinds of photoreceptors: rod cells and cone cells
The objective evaluation results demonstrated that the proposed method is competitive with the state-of-the-art studies and the results of the subjective experiment showed that the proposed method outperforms the state-of-the-art methods in preserving both naturalness and information preservation for individuals with severe red–green color vision deficiency (CVD)
In [24] and [25], textures are added to different areas in original images to improve contrast without changing colors; both normal color vision audiences and CVD audiences are confused whether the textures are imported one or belong to the original image
Summary
The human retina contains two kinds of photoreceptors: rod cells and cone cells. The rod cells are sensitive to lowintensity light. Cone cells play a crucial role in the formation of color vision Anomalies occurring in these cells cause color vision deficiency (CVD) and impair the ability of affected individuals to perceive colors. Image recoloring algorithms [9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27] have been proposed to compensate for CVD and its resulting loss of contrast Some of these studies concentrated on contrast enhancing [9,10,11,12,13,14,15,16,17], while others directed more attention to issues of naturalness preservation [18,19,20,21].
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