Multi-scale retinex-based adaptive gray-scale transformation method for underwater image enhancement

Abstract

Underwater images play an irreplaceable role as one of the carriers of underwater information acquisition. Underwater degraded images are usually affected by the color cast, noise, and blurred details, which are difficult to apply to various vision tasks. We propose a multi-scale retinex adaptive grayscale transformation underwater image enhancement method, which includes three parts: color correction, image denoising, and detail enhancement. Firstly, the multi-scale Retinex algorithm is adopted to extract the lighting components. Mean and mean square errors were introduced through linear quantization, and color recovery factors were adopted to adjust the three channels for color correction. Second, by treating the image as an anisotropic thermal field diffusing in all direction,image noise is eliminated and edge details are preserved. Finally, for different underwater degraded images, a simulated annealing optimization algorithm is introduced to perform adaptive gray-scale transformation on the image to enhance image details. The results show that the proposed method can comprehensively solve the problems of color distortion, noise, and low contrast. Compared with the state-of-the-art underwater image enhancement and restoration methods, our method has achieved better visual effects.