Underwater Image Enhancement Based on Multichannel Adaptive Compensation

Due to underwater light absorption and scattering, underwater images often suffer from color distortion and low contrast. However, existing underwater image enhancement methods can only solve the problem of underwater image degradation in a specific scene and do not consider the impact of dynamic changes in water depth and water quality on underwater image degradation. To solve the above problems, this article proposes a multichannel adaptive fusion underwater image enhancement algorithm. First, to alleviate the color distortion issue caused by light attenuation, this article proposes a gridded adaptive channel compensation algorithm. Subsequently, the compensated image is used for multichannel image enhancement. The first channel image is the enhanced result of the compensated image using the local entropy-constrained gray world algorithm proposed in this article and the second channel image is the enhanced result of the first channel image using the contrast limited adaptive histogram equalization (CLAHE) algorithm. Next, the saliency weight image and brightness weight image of the two-channel images are calculated respectively. Finally, to combine the information advantages of different channel images, this article adopts a Laplacian–Gaussian pyramid to fuse the two-channel enhanced images and their corresponding weight images to obtain the final enhanced image. Experiments on three datasets, LSUI, UIEB, and RUIE, show that the underwater images processed by the algorithm proposed in this article have a good improvement in color and contrast, and robustness is better than the comparative methods. The underwater image quality measure metric (UIQM) value of the enhanced images is 126.844% higher than the original images, the underwater color image quality evaluation metric (UCIQE) value is 66.370% higher than the original images, and the number of ORB feature points is 95.862% higher than the original images. Results are available at
https://drive.google.com/file
.