Image Denoising with Contourlet Transform Based on PCA

被引：2
|
作者：
Sun Lin-li [1 ]
Li Yan [1 ]
Zheng Jian-ming [1 ]
机构：
[1] Xian Univ Technol, Xian 710048, Peoples R China
来源：
ISCSCT 2008: INTERNATIONAL SYMPOSIUM ON COMPUTER SCIENCE AND COMPUTATIONAL TECHNOLOGY, VOL 1, PROCEEDINGS | 2008年
关键词：
multiscale geometry analysis; Contourlet transform; PCA(principal component analysis); denoise;
D O I：
10.1109/ISCSCT.2008.15
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
This paper adopted multiscale geometry method, distilled the principal component from the image after Contourlet transform, lowered the dimension of the high frequency subdomains, eliminated the noise by minimum variance cost function. The entire arithmetic without estimate noise, compared to Contourlet hard threshod denoising and wavelet hard threshod denoising, PSNR increased 1dB, the denoising effect is better than other methods in the experiment.
引用
收藏
页码：31 / 33
页数：3
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