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 via Doubly Local Wiener Filtering Using Directional Windows and Mathematical Morphology

基于小波的图像去噪算法是目前图像处理研究的一个热点。该文提出了一种结合椭圆型方向窗和数学形态学的小波域双重局部维纳滤波图像去噪算法。该算法同时利用了小波域子带的方向信息和图像本身所固有的几何结构:首先使用数学形态学把图像分成纹理区域和光滑区域两部分,然后结合椭圆型方向窗去估计小波域方向子带中每一点的信号方差,最后使用双重维纳滤波器对含噪图像进行去噪。实验结果表明该算法的去噪效果优于其它的采用二维可分离实小波进行图像去噪的算法。

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.