Attenuated color channel adaptive correction and bilateral weight fusion for underwater image enhancement

•A white balance method is proposed for attenuation channel adaptive correction. The WB-ACAC utilizes three indicators derived from the image's RGB channels to identify and select the optimal channel to compensate for the severely attenuated channel adaptively and combines with the gray world method to correct the image color. Compared to existing color correction methods, the WB-ACAC eliminates artifacts and better restores the natural appearance of damaged images.•A local-block-based fast non-local means method is designed. The LB-FNLM introduces the local block to optimize the calculation process, effectively eliminating image noise and significantly reducing computation time.•An adaptive stretching method is proposed based on the histogram's local features. The ASHLF makes full use of the local features of the image histogram by introducing histogram segmentation and cropping techniques. This method optimizes the limitations of the existing global stretching methods and obtains a better contrast enhancement result.•A bilateral weight fusion method is proposed. The BWF selects different weights for the input version image to fully consider the feature differences and generate a fused image with obvious complementary advantages. Due to the absorption and scattering of light and the influence of suspended particles, underwater images commonly exhibit color distortions, reduced contrast, and diminished details. This paper proposes an attenuated color channel adaptive correction and bilateral weight fusion approach called WLAB to address the aforementioned degradation issues. Specifically, a novel white balance method is first applied to balance the color channel of the input image. Moreover, a local-block-based fast non-local means method is proposed to obtain a denoised version of the color-corrected image. Then, an adaptive stretching method that considers the histogram's local features to get a contrast-enhanced version of the color-corrected image. Finally, a bilateral weight fusion method is proposed to fuse the above two image versions to obtain an output image with complementary advantages. Experimental studies are conducted on three benchmark underwater image datasets and compared with ten state-of-the-art methods. The results show that WLAB has a significant advantage over the comparative methods. Notably, WLAB exhibits a degree of independence from camera settings and enhances the precision of various image processing applications, including key