A Novel Wavelet-based Denoising Method of SAR Image Using Interscale Dependency

Addressing SAR image speckle denoising, this dissertation proposes a new method based on bivariate shrinkage function combined with enhancement of wavelet significant coefficients, which allows us to consider the dependencies between coefficients. In our paper we make the speckle noise model suit the bivariate shrinkage function, and the joint probability density functions (PDF) and noise PDF could be united by MAP to de-noise image, then the wavelet coefficients are enhanced according to a rule whether the coefficient is a significant one or not. The simulation demonstrates that the new algorithm has a better denoised effect comparing with other traditional denoising methods.