ZAP: Underwater Image Color Correction via Zero Approximation Principle
Baiqiang Yu, Weidong Zhang, Wenqiang Yu, Peixian Zhuang, Wenyi Zhao · IEEE Geoscience and Remote Sensing Letters · 2024
Underwater images widely endure severe color distortion because of the absorption and scattering of the water medium. We present a zero-approximation principle for underwater image color correction, called ZAP, to tackle this issue. Specifically, we first present the channel’s a and b pixel values to subtract the corresponding channels’ average pixel values so that the histograms corresponding to their pixel values are symmetric about the zero within the CIELab model. Afterward, we utilize the standard deviation of the channels’ a and b compensated pixel values to adjust the channels’ dynamic range and correct the image color distortion. Broad qualitative and quantitative experiments prove the practicability of ZAP for correcting color distortion in underwater images.