Ultrasound Speckle Reduction via Super Resolution and Nonlinear Diffusion

Bo Wang, Tian Cao, Yuguo Dai, Dong C. Liu

Abstract: Recently, some diffusion-based filtering methods have been developed such as anisotropic diffusion (AD) or nonlinear diffusion (ND), which can reduce the speckle noise, at the same time, preserve and enhance the edge/borders in ultrasound image. However, because of the granular pattern of speckle, it is quite difficult to reduce speckle exactly through diffusion-based methods only. In this paper, we propose a super resolution (SR) based ND method. We firstly reduce and compound speckle noise in a sequence of ultrasound images by using a fast SR method for ultrasound image. After this process, ultrasound speckle is much smaller, and the edge and structure are much clearer as complementary information of different images was used. To reduce the noise of the SR improved image, we use a local coherence based ND method. In the end, experimental results of the proposed method are compared with some other AD methods to demonstrate its effectiveness.