A Preprocessing Algorithm based on Wavelength Adaptive White Balance and Enhanced Dark Channel Prior to Processing Underwater Images

Abstract

In order to overcome the problems of the bluish-green tone of color, bad contrast, and bad texture of underwater pictures, we introduced a two-step lightweight enhancement algorithm called WAWB-IDCP. The algorithm uses the wavelength-based white balance and an enhanced dark channel post-module, which contribute to the correct color correction and optimization of image quality, respectively. It solves the problem of color distortion and artifacts in blocks seen in traditional DCP algorithms. Experiments with multi-dimensional references were performed on three classic algorithms (Gray-world, CLAHE, DCP). The experimental results on the UIEB dataset prove that our algorithm has the highest subjective visual performance and also performs well on other quantitative measures, like the standard deviation of the algorithm of 44.71 and color cast control of 11.07. Furthermore, the SIFT feature experiment proves that it has a great capacity for recovering details and is also noise-resilient. The algorithm is highly performing and can be used in preprocessing underwater images.