Side-scan sonar image denoising method based on improved NLM algorithm

Abstract

Side-scan sonar is widely used in maritime search and rescue, submarine geological exploration, target detection and identification, etc. with its long range of action, comprehensive coverage, and large amount of collected data. Image denoising is the premise of the correct interpretation of side-scan sonar images. In this paper, a new weighted kernel function is proposed on the basis of the original Non-Local Means (NLM) denoising algorithm, which leads to an improved non-local mean denoising algorithm. By experimenting with Gaussian white noise images with different noise levels, it appears that the efficiency of this algorithm is superior to that of the NLM algorithm, and the denoising performance is significantly enhanced compared with the NLM and Fast Non-Local Means (FNLM) algorithm, especially for images under solid noise.