Abstract: “A robust wavelet domain method for noise filtering in medical images is one of the techniques used to reduce the noise. The method adapts various types of image noise as well as to the preference of the medical expert: a single parameter is being used to balance the preservation of (expert-dependent) relevant details against the degree of noise reduction. A versatile wavelet domain despeckling technique to visually enhance the medical ultrasound (US) images for improving the clinical diagnosis is used. The method uses the two-sided generalized Nakagami distribution (GND) for modeling the speckle wavelet coefficients and the signal wavelet coefficients are approximated using the generalized Gaussian distribution (GGD) [1]. Combining these statistical priors with the Bayesian maximum a posteriori (MAP) criterion, the thresholding/shrinkage estimators are derived for processing the wavelet coefficients of detail subbands. Consequently, two blind speckle suppressors named as GNDThresh and”

Keywords: Genetic Algorithm, Image Enhancement, Speckle Noise.