利用数学形态学和复数小波方向窗维纳滤波的图像去噪算法

Wavelet-Based Image Denoising via Wiener Filtering Using Complex Wavelet Directional Windows and Mathematic Morphology

利用小波进行图像去噪是目前图像处理研究的热点。提出了一种结合数学形态学和复数小波方窗维纳滤波的图像去噪算法。该算法同时利用了复数小波的方向特性和图像本身固有的几何特性,首先使用双树复数小波变换对图像进行处理,再在基于复数小波域上进行维纳滤波,接着使用数学形态学把图像分成光滑区域和纹理区域2个部分,然后结合复数小波方向窗去更准确地估计小波域方向子带每一点的信号方差,最后利用维纳滤波器进对含噪图像进行去噪处理。实验结果表明,该算法的去噪效果优于一般的复数小波维纳滤波,并且运算更加简洁。

In image processing spplications applications wavelet-based image denoising algorithms is a hot point.In this paper,a Wiener filtering using complex wavelet directional windows and mathematic morphology is proposed,in which the image is processed by a tree complex wavelet,and wiener filtering with complex wavelet,and the mathematical morphology is first used to divide the image into texture and smooth regions,and then combine the complex wavelet directional windows to estimate the signal variance of each wavelet coefficients in different oriented sub-bands.Finally the 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 wiener filtering with complex wavelet,and the operation is more simple and direct.