基于Contourlet变换和Wiener滤波的图像降噪

Image Denosing Based on Contourlet Transform and Wiener Filter

提出一种新的基于Contourlet变换和Wiener滤波的图像降噪方法。该方法充分利用Contourlet变换域系数服从广义高斯分布的特点,在Contourlet域采用Bayes收缩阈值法进行预降噪,采用Wiener滤波法对预降噪图像中的残留噪声进行进一步处理,以提高图像的恢复精度。仿真结果表明,该方法较传统的Contourlet域降噪方法具有更好的降噪效果,进一步提高了PSNR值,降低了MSE值,获得了更好的图像恢复质量。

A new image denosing method based on Contourlet transform and Wiener filtering is proposed. By using the statistical information, the Contourlet domain coefficients of the original image are estimated by Bayes shrink threshold algorithm. For further denoising, the final denoising image will be estimated through Wiener filtering. Experimental results show that the denoising effect of this method is better than that of other methods based on Contourlet transform.