Multiresolution image denoising based on wavelet transform

Wavelet-based image denoising is very attractive to analysis and synthesis functions. It enables us to divide a complicated function into several simpler ones and study them individually. In this paper, we present a new image-denoising algorithm based on multiresolution local contrast entropy of the wavelet coefficients. We introduce a new adaptive threshold estimation depending on the probability distribution of the noise in the wavelet coefficients. This threshold enables the proposed algorithm to be adaptive to unknown smoothness of the denoising images. The experiment confirms that the proposed approach is cable of achieving good results for additive white Gaussian noise.