Side-scan sonar image despeckling based on block-matching and 3D filtering
侧扫声呐图像的3维块匹配降斑方法

Speckle noise is the major factor affecting the quality of side-scan sonar images. Side-scan sonar image despeckling has therefore a great significance to object identification and image processing.According to side-scan sonar image characteristic and distribution of speckle noise,a despeckling method based on block-matching and 3D filtering (BM3D) is proposed in this paper.A Rayleigh distributed multiplicative speckle noise model is established according to a seabed scattering model.Rayleigh distributed of speckle noise is changed into Gaussian distribution by the Gaussian smooth function power transform.The multiplicative noise is changed into additive noise by a logarithmic transform.Then,the transformed images are filtered by an efficient BM3D algorithm.Last,the final images are achieved by inverse transform.The experimental results show that the new algorithm has a better performance in terms of edge preserving and denoising than other spatial filtering,wavelet and Curvelet domain filtering methods.