Underwater Image Enhancement Based on Image Segmentation and Color Adaptation Transformation for White Balance

Owing to the effects of absorption, scattering, and attenuation during underwater light propagation, images acquired from an underwater scene degenerate significantly, i. e. , they exhibit low contrast and undesirable blue-green bias. Therefore, an underwater image enhancement algorithm based on image segmentation and color adaptation transformation for white balance is proposed. The color adaptation transformation is introduced for underwater color correction, and a low illumination enhancement method based on three-channel inversion defogging is applied to improve underwater images. Further, a white balance strategy based on image segmentation is proposed, and the proposed algorithm is compared with classical algorithms. Experimental results show that the average values of the underwater color image quality evaluation metric (UCIQE), underwater image quality measures (UIQM), and neutral color angle error of the image processed by the proposed algorithm are 0. 5839, 1. 3689, and 5. 0972 respectively, which are higher than those of two classical algorithms. The proposed algorithm presents certain advantages in terms of color correction and sharpness improvement.