Wavelet-based image denoising using three scales of dependency

The denoising of a natural image corrupted by the Gaussian white noise is a classical problem in image processing. A new image denoising method is proposed by using three scales of dual-tree complex wavelet coefficients. The dual-tree complex wavelet transform is well known for its approximate shift invariance and better directional selectivity, which are very important in image denoising. Experiments show that the proposed method is very competitive when compared with other existing denosing methods in the literature.