Image Denoising Based on Non-based Estimator of Local Variance for Complex Wavelet Coefficients
基于复小波系数局部方差无偏估计量的图像去噪

In order to effective denoising, this paper proposes a new computationally feasible adaptive noise-smoothing algorithm that considers the local dependency characteristics of images under the complex dual-tree discrete wavelet transform (DWT). The variances of local statistics are estimated with a centered square-shaped window for each coefficient. Previous denoising algorithms tend to smear edges severely in the filtered result. The new denoising algorithm overcomes this problem. Some comparisons with the best available results will be given in order to illustrate the effectiveness of the proposed algorithm.