基于Contourlet和Bandelet混合变换的图像去噪

Beibei Song, Lu-ping Xu, Wenfang Sun
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引用次数: 13

摘要

提出了一种新的多尺度多方位图像表示方法——CBlet变换。它将新的轮廓波变换与第二代带宽化方法相结合。其中,contourlet变换捕获图像不连续点并将其连接成线性结构,然后bandeleization过程采用线性结构跟踪并进一步去除它们之间的相关性。在相同的冗余度下,CBlet变换比contourlet变换得到了更稀疏的表示。图像去噪的数值实验表明,所提出的CBlet变换在PSNR和视觉质量上都优于新的contourlet变换。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Image Denoising Using Hybrid Contourlet and Bandelet Transforms
This paper proposed a new multiscale and multidirectional image representation method named CBlet transform. It combines the new contourlet transform with the second-generation bandeletzation procedure. Thereinto, the contourlet transform captures image discontinuous points and links them into linear structures, then the bandeletization procedure pursuits the linear structures adoptively and further removes their correlation. The CBlet transform obtains much sparser representation than the new contourlet transform at the same redundancy. Numerical experiments on image denoising show that the proposed CBlet transform can outperform the new contourlet transform both in term of PSNR and in visual quality.
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