Striped noise suppression in side-scan sonar images based on improved Criminisi algorithm

In response to the problem of striped noise in side-scan sonar images caused by oceanic and electronic noise interference, as well as the issues of high computational complexity, insufficient universality, and blurry imaging effects in traditional methods for processing striped noise in side-scan sonar images, a fringe noise suppression method for side-scan sonar images based on the improved Criminisi algorithm is proposed in this paper. Considering that side-scan sonar images are mainly composed of background and repetitive textures, the algorithm replaces global image search with setting appropriate search radii for local search, thereby improving computational efficiency. Through experiments conducted on simulated and real striped noise images, and comparisons with four classic methods, Fourier Transform, which significantly improves denoising effects, simulated noise image 1 shows an increase in PSNR and SSIM values of 2.2% and 1.79% respectively, while simulated noise image 2 shows an increase of 5.21% and 5.87% respectively.