Abstract: In this paper,a new image denoising algorithm via doubly local Wiener filtering with windows based on Stationary Wavelet Transform（SWT） with the Dual Tree Complex Wavelet Transform（DTCWT） is proposed.In the first stage of Wiener filtering,the noisy image is decomposed by SWT.Then,the signal variances of wavelet coefficients are estimated in the elliptic windows.In the second stage of Wiener filtering,the image restored by Inverse SWT（ISWT） is decomposed by DTCWT.Then,the adaptive windows determined by the autocorrelation function of wavelet coefficients’ energy distribution are used to estimate the signal variance of wavelet coefficients.Finally,the image is restored by Inverse DTCWT（IDTCWT）.Experimental results and analysis are given to demonstrate the validity of the proposed algorithm.

Key words: DTCWT, elliptic directional windows, adaptive windows, doubly local Wiener filtering, noise reduction

摘要： 提出了一种基于静态小波变换和对偶树复小波变换的加窗的双重局部维纳滤波图像去噪算法。在第一次局部维纳滤波中,用静态小波变换对含噪图像进行分解,然后利用椭圆方向窗来估计不同方向子带的各点信号的方差;在第二次的局部维纳滤波中,第一次局部维纳滤波恢复后的图像被对偶数复小波变换分解后,利用由子带能量自相关函数确定的自适应窗来估计不同方向子带的各点信号的方差,然后利用逆对偶数复小波变换对图像进行恢复。实验结果及分析表明了该去噪算法的有效性。

关键词: 对偶树复小波变换, 椭圆方向窗, 自适应窗, 双重局部维纳滤波, 图像去噪