Underwater image processing method based on red channel prior and Retinex algorithm

Abstract

Due to light being absorbed by water and scattered by suspended particles, color distortion, low image contrast, and detail loss are the common problems found in underwater images. We present an underwater image processing method, which based on an underwater imaging model, makes initial image restoration with the improved red channel prior combining transmission reduction, background light correction, and color compensation to acquire clearer underwater images, and then combines multiscale retinex (MSR) enhancement and hue saturation value to enhance image color contrast and saturation. Results indicate that, compared with the original images, the method proposed in this paper is capable of significantly enhancing image definition, saturation, contrast, and luminance. In comparison with dark channel prior, single-scale retinex (SSR), MSR, and multiscale retinex with color restoration (MSRCR), this method greatly improved the average gradient of images while keeping the information entropy of images unchanged. The average gradient calculated with the proposed method increased by 239%, 199%, 200%, and 220% for the three given images, respectively, compared with the other methods above.