基于平稳Contourlet变换的图像去噪方法

The Image Denosing Via Stationary Contourlet Transform

多尺度几何分析中的Contourlet变换可以实现灵活的多分辨、多方向图像表示,但是由于不具有平移不变性,在图像去噪中容易产生伪吉布斯现象,本文应用具有平移不变性且能有效表示图像纹理信息的平稳Contourlet变换,提出了软硬阈值结合的去噪法.试验结果表明该方法有效提高去噪声后图像的PSNR,有效保存图像纹理信息以及更好的视觉效果.

Contourlet transform （CT） is a method of multiscale geometric analysis, which can result in a flexible multri-resolution ,local ,and directional image expansion. But the Controulet transform is not shift- ubvaruabt,that will cause pseudo-Gibbs phenomena around singularities in image denoising. In this paper we apply stationary contourlet transform with shift - invariant to image denosing,which can capture the intrinsic geometrical structure of image. In the test o Image denoising we apply the modified desosing method by threshold. The experimental results show that our method can get higher PSNR value and better visual effect compared with other methods.