Enhancing Underwater Images via Color Correction and Multiscale Fusion

Abstract

Color distortion, low contrast, and blurry details are the main features of underwater images, which can have adverse effects on their quality. To address these issues, a novel enhancement method based on color correction and multiscale fusion is proposed to improve underwater image quality, achieving color correction, contrast enhancement, and detail sharpening at different stages. The method consists of three main steps: color correction using a simple and effective histogram equalization-based method to correct color distortion, decomposition of the V channel of the color-corrected image into low- and high-frequency components using a guided filter, enhancement of the low-frequency component using a dual-interval histogram based on a benign separation threshold strategy, and a complementary pair of gamma functions; the fusion of the two versions of the low-frequency component to enhance image contrast; and finally, the design of an enhancement function to highlight image details. Comparative analysis with existing methods demonstrates that the proposed method achieves high-quality underwater images and favorable qualitative and quantitative evaluations. Compared to the method with the highest score, the average UIQM score of our method exceeds 6%, and the average UCIQE score exceeds 2%.