Paper
4 February 2013 Correcting saturated pixels in images based on human visual characteristics
Author Affiliations +
Proceedings Volume 8660, Digital Photography IX; 866009 (2013) https://doi.org/10.1117/12.2008310
Event: IS&T/SPIE Electronic Imaging, 2013, Burlingame, California, United States
Abstract
This paper presents a correcting method for saturated images which is operated in the YCbCr color space. The algorithm is based on two human visual characteristics, one is the visual sensitivities to color differences and the other is the Hunt effect. During the process of correcting colors, MacAdam ellipse model mapped to the YCbCr color space is used to search the nearest color. And during the process of the quantification of the YCbCr components for digital implementation, the regions with high luminance are set to have less saturation based on the Hunt effect. Experimental results show that the proposed method is more effective in correcting saturated pixels, especially for the optimization of the region with less luminance and more colorfulness.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jun Fu, Hui Peng, Xi Chen, and Xuanqin Mou "Correcting saturated pixels in images based on human visual characteristics", Proc. SPIE 8660, Digital Photography IX, 866009 (4 February 2013); https://doi.org/10.1117/12.2008310
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Chromium

RGB color model

Visualization

Distortion

Color difference

Color vision

Eye models

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