Pyramid based multiscale anisotropic diffusion filter for ultrasound image despeckling

Abstract

The ultrasound image is significantly degrade by the coherence speckle. A pyramid based multiscale anisotropic diffusion filter is proposed for medical B-mode ultrasound image despeckling. In the Laplacian pyramid domain, according to the different bandpass ultrasound image characteristics in each layer, the anisotropic diffusion filter is adaptively performed to suppress the speckle. For the anisotropic diffusion, the speckle scale function is estimated in the homogeneous area in each layer and the number of iteration is automatically determined by the Mean Absolute Error (MAE). The performance of the proposed method has been compared with that of other state-of-the-art methods, including the speckle reducing anisotropic diffusion, the nonlinear coherence enhance diffusion and the nonlocal means filter. The preliminary results of both simulated images and real ultrasound B-mode images indicate that the proposed method could effectively remove the speckle while preserving the edge and details.

Image Denoising Based on Adaptive Fractional Order with Improved PM Model

“…The anisotropic diffusion filter has received much attention since it was first proposed by Perona and Malik in 1990, which is called Perona-Malik model (PM model) [1]. In the classical PM model, the gradient value is used in the direction of east, west, south, and north to distinguish variations which are caused by noise or edge in a corrupted image [2]. The shortcomings of PM model are that the model is easy to lose contrasting information and texture information and produce staircase effects [3].…”