资料下载
基于Contourlet变换尺度间相关的图像去噪
刘润生
分享资料个
Contourlet域数据分析表明，信号的变换域系数在尺度间相关性高，而白噪声则呈弱相关
或不相关。通过相关性强弱区分噪声与信号系数，并结合闽值函数，提出了基于Contourlet变换尺度间相关的图像去噪新算法。实验结果表明，新方法去噪后的图像比小波相关去噪算法的PSNR值更高，视觉效果更好，尤其适用于纹理轮廓丰富的图像去噪。
Analyses of Contourlet coeficients indicate that inter-scale contourlet coeficients with
respect to signals are highly correlated while the correlations associated with white noise are less or even do not exist．According to the property,an image denoising algorithm based on inter-scale corelations of Contourlet COOficients iS proposed combined with threshold functions．Experimental results show that the proposed method outperforms the coresponding wavelet method in term s of both peak-signal—to-noise(PSNR)and visual quality,and it is especially adequate to the images with much texture．
声明：本文内容及配图由入驻作者撰写或者入驻合作网站授权转载。文章观点仅代表作者本人，不代表电子发烧友网立场。文章及其配图仅供工程师学习之用，如有内容侵权或者其他违规问题，请联系本站处理。 举报投诉
- 相关下载
- 相关文章
