Ultrasound speckle suppression and edge enhancement using multiscale nonlinear wavelet diffusion

This paper introduces a novel multiscale nonlinear wavelet diffusion (MNWD) method for ultrasound speckle suppression and edge enhancement. It considers wavelet diffusion as an approximation to nonlinear diffusion within the framework of the dyadic wavelet transform. Consequently, this knowledge is exploited in the design of a speckle suppression filter with an edge enhancement feature. MNWD takes advantage of the sparsity and multiresolution properties of wavelet, and the iterative edge enhancement feature of nonlinear diffusion. In our algorithm, speckle is suppressed by employing the iterative multiscale diffusion on the wavelet coefficients, while the edges of the image are enhanced by using an iterative signal compensation process. We validate the proposed method using synthetic and real echocardiographic images. Performance improvement over other traditional denoising filters is quantified in terms of noise suppression and structural preservation indices. The application of the proposed method is demonstrated by the segmentation of the echocardiographic image using the active contour.