Experiments with Wavelet based Image De-noising using Generalized Cross Validation

De-noising algorithms based on wavelet thresholding replace small wavelet coefficients by zero and keep or shrink the coefficients with absolute value above the threshold. The optimal threshold minimizes the error of the result as compared to the unknown, exact data. To estimate this optimal threshold, we use Generalized Cross Validation. This procedure does not require an estimation for the noise energy. Originally, this method assumes uncorrelated noise, and an orthogonal wavelet transform. In this paper we investigate the possibilities of this method for less restrictive conditions.