Non-subsampled contourlet transform based spatially adaptive shrinkage for speckle reduction of medical ultrasound image

Speckle is a multiplicative noise that degrades ultrasound images. In this paper, a statistical spatially adaptive approach for speckle reduction in medical ultrasound images based posterior conditional means (PCM) estimation in the nonsubsampled contourlet domain is proposed. In this framework, a new class of statistical model for nonsubsampled contourlet coefficients is proposed. And the proposed method uses the Gaussian distribution for speckle noise and normal inverse Gaussian distribution for modeling the statistics of nonsubsampled contourlet coefficients in a logarithmically transformed ultrasound images. Experiments are carried out using synthetically speckled and real ultrasound images. The experimental results demonstrate that the proposed method performs better than several other existing methods in terms of quantitative performance as well as in term of visual quality of the images.