Wavelet-Based Image Denoising via Doubly Local Wiener Filtering Using Directional Windows and Mathematical Morphology
利用数学形态学和方向窗的小波域双重局部维纳滤波图像去噪算法

Wavelet-based image denoising algorithms is a hot point in image processing applications. In this paper, a doubly local Wiener filtering algorithm using elliptic directional window and mathematical morphology is proposed, in which the mathematical morphology is first used to divide the image into texture and smooth regions, and then combine the elliptic directional window to estimate the signal variance of each wavelet coefficients in different oriented subbands, finally the doubly local Wiener filtering is used to denoise the observed image. Experiment results show that the proposed algorithm is better than the existing image denoising algorithms using 2-D real separable wavelets.