Underwater image denoising based on curved wave filtering and two-dimensional variational mode decomposition

Abstract

Underwater image denoising technology is of great significance in underwater operation. Underwater operations (such as offshore oil drilling, undersea tunnels, pipeline construction, underwater archaeology, biological research, and lifesaving) require stable and clear underwater images to aid analysis. Due to the scattering and absorption of light by water bodies, obtaining high-quality underwater images is a challenging task. Underwater images are prone to low contrast, low resolution and edge distortion. Therefore, it is difficult to accurately separate the effective signal when removing the underwater image noise, which leads to the image contrast reduction. Also the edge contour is not clear, and the detail loss is serious. Therefore, we propose a novel underwater image denoising method based on curved wave filter and two-dimensional variational mode decomposition. Firstly, the noisy image is decomposed by two-dimensional variational mode decomposition, and a series of modal components with different center frequencies are obtained. The effective modal components are selected by correlation coefficient and structural similarity. And the effective modal components are processed by the curve-wave filter. Finally, the filtered modal components are reconstructed to remove the noise in the image. The experimental results show that, compared with other state-of-the-art methods, the proposed method has clearer denoising results, less mean square error, and better denoising effect.