基于块自适应窗的小波域维纳滤波图像去噪

基于图像经小波分解后细节子带能量簇的主方向由边缘方向、纹理方向和子带滤波器的方向选择性共同决定这一事实，提出了基于块自适应窗的小波域维纳滤波图像去噪算法。对含噪图像进行离散小波变换后，对每一层三个细节子带分别无重叠分块，利用细节子带块能量相关函数确定每一块中能量簇的主方向及相应的块自适应窗口，在得到的块自适应窗口中估计不同方向块中各点信号方差，进而对子带系数进行维纳滤波，得到细节系数的估计，然后进行小波逆变换，得到去噪图像。实验结果表明了该方法比基于矩形窗口的小波域局部维纳滤波有更好的去噪效果。

Image Denoising Algorithm Using Local Wiener Filtering with Block-Adaptive Windows in Wavelet Domain

In this paper, we propose the block-adaptive windows that are used to upgrade the image denoising performance of the local Wiener filtering method. Based on the fact that the energy clusters in the detail subimages of an image exhibit direction features varying with spatial locations and oriented subbands, a noisy detail subimages is divided into non-overlapping small- size blocks and the spatial energy correlations function of each block is calculated to determine the principal direction of energy clusters within each block and the corresponding block - adaptive window. The block - adaptive windows are used to improve the estimations of the image＇s energy distribution in the detail subimages. The experimental results show that the local Wiener filtering method with block - adaptive windows is superior to other local Wiener filtering methods using square window.