Optimum threshold parameter estimation of wavelet coefficients using fisher discriminant analysis for speckle noise reduction

Optimizing threshold value of wavelet coefficient is an important task in speckle noise reduction in the wavelet domain. Without proper selection of threshold value image information may be lost, which is unwanted. In this paper we proposed optimum threshold parameter using Fisher Discriminant Analysis (FDA) for determining the optimum threshold value of wavelet coefficient for the best speckle noise reduction. It also preserves edges without destroying image information. The method is compared with the several other classical thresholding methods on variety of images and the experimental results confirm significant improvement over existing methods.