Correcting saturated pixels in images based on human visual characteristics

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.