Underwater Optical Image Contrast Enhancement via Color Channel Matching

Xiaoguo Chen, Shilong Sun, Yaqi Gao, Wenyi Zhao, Weidong Zhang

Abstract: Due to the complex physical environment underwater, underwater captured images often suffer from issues such as color distortion, low contrast, and loss of texture details. To address this issue, we propose a color channel matching (CCM) method for underwater optical image contrast enhancement, called CCM. Specifically, we first convert the raw image into a grayscale image and employ histogram matching techniques to make the brightness distribution of the image more uniform, thereby reducing brightness variations caused by environmental factors. Then, we transform the matched image into the hue-saturation-intensity (HSI) color space and optimize the HSI channels separately. During this process, we decouple the intensity information from the color information to avoid interference during enhancement, which employs adaptive histogram equalization on the intensity channel to improve contrast and detailed representation further. Finally, we fuse the processed intensity channel with the optimized hue and saturation channels to obtain the final contrast-enhanced image. Extensive qualitative and quantitative experimental results demonstrate that the proposed method exhibits strong robustness and generalization capabilities in enhancing the contrast of underwater images.

External IDs:dblp:journals/lgrs/ChenSGZZ25