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基于Contourlet变换和Wiener滤波的图像降噪
Image Denosing Based on Contourlet Transform and Wiener Filter
【摘要】 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。
【Abstract】 A new image denosing method based on Contourlet transform and Wiener filtering is proposed. By using the statistical information, theContourlet domain coefficients of the original image are estimated by Bayes shrink threshold algorithm. For further denoising, the final denoisingimage will be estimated through Wiener filtering. Experimental results show that the denoising effect of this method is better than that of othermethods based on Contourlet transform.
【关键词】 图像处理;
Contourlet变换;
Wiener滤波;
预降噪图像;
【Key words】 image processing; Contourlet transform; Wiener filtering; pre-denoised image;
【Key words】 image processing; Contourlet transform; Wiener filtering; pre-denoised image;
【基金】 国家自然科学基金资助项目(60472103);上海市优秀学科带头人基金资助项目(05XP14027);上海市重点学科基金资助项目(T0102)
- 【文献出处】 计算机工程 ,Computer Engineering , 编辑部邮箱 ,2008年05期
- 【分类号】TN911.73;TP391.41
- 【被引频次】3
- 【下载频次】259