Despeckling of medical ultrasound kidney images in the curvelet domain using diffusion filtering and MAP estimation
An algorithm to reduce speckle has been proposed in the undecimated curvelet domain. Maximum A posteriori Probability Technique with the priori probability assumption as Gaussian is used to estimate the shrinkage function. Part of the curvelet coefficients are modelled using the estimated shrinkage function, whereas rest of the coefficients are diffusion filtered. Proposed method is compared with popular spatial domain filters, wavelet and curvelet domain methods quantitatively.
despeckling diffusion filter map estimation curvelet transform coefficient modeling