A Novel Despeckling Method Based on Multiscale Analysis for Ultrasound B-Mode Imaging

Ultrasound (US) imaging is one of the most powerful technique for visualizing internal organs and soft tissues in the human body. The presence of speckle noise in US image makes the diagnostic more difficult, therefore to overcome this problem, Laplacian pyramid-based speckle reducing anisotropic diffusion (LPSRAD) method is proposed in this paper. With this method, speckle noise is removed in ultrasound images by bandpass of speckle reducing anisotropic diffusion filter in Laplacian pyramid domain for improving the image quality and increasing the accuracy in image interpretation and analysis. Various speckle reduction methods, viz., Perona Malik (PM), Laplacian pyramid-based non-linear diffusion (LPND), the Bayesian nonlocal means filter (OBNLM) and Speckle Reducing Anisotropic Diffusion (SRAD) are compared with the proposed LPSRAD method. Experiments have been conducted on phantom, simulation and in vivo images and the performance measures such as structure similarity (SSIM), signal-to-noise ratio (SNR), mean square error (MSE) and peak signal-to-noise ratio (PSNR) were calculated. The results show that the proposed method could maintain edges and boundaries in effective manner as very well suppressing speckle at the same time.