Wavelet Decomposition–Based Speckle Reduction Method for Ultrasound Images by Using Speckle-Reducing Anisotropic Diffusion and Hybrid Median

Abstract

Ultrasound imaging is considered as a common facility of imaging techniques used in medical field because of its benefits, but the quality of ultrasound image is affected and degraded by the type of noise generated by the backscattered signals that interfere with each other and introduce a random interference pattern. This pattern is called speckle. In this article, we develop a new denoising method by introducing a speckle-reducing anisotropic diffusion filter into 4 sub-band images gained by using 2-dimensional wavelet decomposition. Moreover, according to frequency content on each sup band, we use hybrid median filter to get a full advantage of using nonlinear filtering in speckle noise. Finely to improve the quality of image and the overall performance, total variation is used in view of it is capability of brightness equality and edges preserving. The experimental result shows that the proposed method is highly effective in noise separation as well as edges preserving based on compression between linear scaling of the gray-level values despeckle filter, speckle-reducing anisotropic diffusion, median, hybrid median filter, and wavelet filters using image quality evaluation metrics.