Multi-scale image denoising based on goodness of fit (GOF) tests

A novel image denoising method based on discrete wavelet transform (DWT) and goodness of fit (GOF) statistical tests employing empirical distribution function (EDF) statistics is proposed. We formulate the denoising problem into a hypothesis testing problem with a null hypothesis corresponding to the presence of noise, and alternate hypothesis representing the presence of only desired signal in the image samples being tested. The decision process involves GOF tests, employing statistics based on EDF, being applied directly on multiple image scales obtained from DWT. We evaluate the performance of the proposed method against the state of the art in wavelet image denoising through extensive experiments performed on standard images.