A Reverberation Noise Suppression Method of Sonar Image Based on Shearlet Transform

Abstract

A sonar image affected by reverberation noise would generate serious speckle noise in the image, which causes great trouble for the later sonar image target segmentation and detection. Therefore, noise suppression is a crucial preprocessing technique for sonar image applications. To suppress the reverberation noise effectively in the sonar image, a reverberation noise suppression method of sonar image based on shearlet transform is proposed. First, to effectively apply the noise suppression method to sonar images, a method of combining the transform from the reverberation noise model to the Gaussian additive noise model with the shearlet transform is presented. Second, in the process of the shearlet transform, constructing a shear wave filter based on the Meyer window function, which has an excellent performance in both time and frequency domains, is suggested. Third, a noise variance estimation based on weak texture blocks would be made to avoid the effect of gray overflow in sonar images. Then, the estimated variance is combined with the root mean square coefficient obtained from the shearlet transform of the simulated noise. For this reason, obtaining the adaptive filtering thresholds of each scale and each direction is essential. With this process, a better reverberation suppression effect could be achieved. Simulation and experimental results demonstrate that the method proposed in this article can suppress reverberation noise more effectively, and a better edge-preserving effect could be obtained. Compared with other comparison algorithms, the algorithm proposed in this article could achieve the best results on the peak signal-to-noise ratio (PSNR) and SSMI.