Anisotropic diffusion filtering for ultrasound speckle reduction

Abstract

Speckle noise has long been known as a limiting factor for the quality of an ultrasound B-mode image. In this study, anisotropic diffusion filtering is proposed as an effective method for ultrasound speckle reduction. This article provides a brief description of anisotropic diffusion filtering proposed by Perona and Malik, and compares its speckle filtering effects with other filtering methods including median, moving average, and frequency domain Gaussian low-pass. In this study, multiple filters are implemented in Matlab. For each filter, three different types of noisy images with speckle noise are tested. The results show that anisotropic filter can reduce the noise more effectively and meanwhile preserve the boundaries of the objects. In addition, this filter has more controllable filtering parameters and is independent on the information of the noise.