Wavelet-based Despeckling of Medical Ultrasound Images

Abstract

This paper presents a new wavelet-domain technique for despeckling of medical ultrasound (US) images for improved clinical diagnosis. The method uses the generalized Gaussian distribution and generalized gamma distribution to model the image and the speckle, respectively, in the detailed sub-bands of wavelet decomposition of the log-transformed US image. Combining these, a priori distributions with the Bayesian maximum a posteriori criterion, shrinkage estimators are derived for processing the wavelet coefficients of the detail sub-bands. The visual comparison of despeckled US images and the higher values of quality metrics indicate that the new method suppresses the speckle noise well while preserving the texture and organ surfaces.