Wavelet multiplicative noise image nonlinear filtering technique

A new nonlinear image filtering technique for multiplicative noise in the wavelet transform domain is presented. Unlike most existing techniques, this approach does not require prior modeling of either the image or the noise statistics. This approach explicitly accounts for the signal dependent nature of the noise. This is considered by attempting to use the variance of the detail wavelet coefficients to decide whether to smooth or preserve these coefficients. The algorithm uses the statistical approach of analysis of variance to decide whether detail wavelet coefficients are due to image related features or they are due to noise. Results of our approach show that the proposed algorithm outperforms other conventional techniques.