[1]王敏,周树道,叶松..基于小波变换方向信息的奇异值图像去噪研究[J].郑州大学学报(工学版),2012,33(03):121-124.[doi:10.3969/j.issn.1671-6833.2012.03.031]
　WANG Min,ZHOU Shudao,YE Song.Image Denoising Based on Wavelet Transform Direction and SVD[J].Journal of Zhengzhou University (Engineering Science),2012,33(03):121-124.[doi:10.3969/j.issn.1671-6833.2012.03.031]
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基于小波变换方向信息的奇异值图像去噪研究()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
33
期数:
2012年03期
页码:
121-124
栏目:
出版日期:
2012-05-10

文章信息/Info

Title:
Image Denoising Based on Wavelet Transform Direction and SVD
作者:
王敏; 周树道; 叶松.
解放军理工大学 气象学院,江苏南京,211101, 解放军理工大学 气象学院,江苏南京,211101, 解放军理工大学 气象学院,江苏南京,211101
Author(s):
WANG Min; ZHOU Shudao; YE Song
instibute of Meteorology, PLA University of Scienee and Technology, Nanjing 211101, China
关键词:
图像去噪;  小波变换;  奇异值分解;  滤波;  小波重构
Keywords:
wavelet transform: singular value decomposilion;  image denoising: filtering;  wavelet reconstruction
分类号:
TN911.73
DOI:
10.3969/j.issn.1671-6833.2012.03.031
摘要:
提出一种基于小波变换方向信息的奇异值图像分解去噪方法.由于图像噪声主要集中在小波域中的高频子图部分,且系数较小,可以利用奇异值分解后较大的奇异值和对应的特征向量重构出去噪图像,然而由于奇异值分解固有的行列方向性,对于高频对角线子图重构出的图像去噪效果不理想,故采取旋转至行列方向后再进行常用的奇异值滤波.低频子图仅作简单维纳滤波,最后将去噪后的低频和高频子图进行小波反变换重构出最终的去噪图像.实验结果表明,该方法在有效去噪的同时较好地保留了原有的高频细节信息.
Abstract:
An optimized image denoising algorithm is proposed based on wavelet transform direetional information and SVD, As the image noise is mainly concentrated in the high-frequeney, and the coefficient is smalluging singular value decomposition of large singular values and corresponding eigenvectors reconstructed imagenoise out, but because of the inherent direction of the singular value decomposition, denoising result of diagonal sub-image reconstructed is not satisfactory, we rotate the diagonal sub-image to the level ( verlical) ,thenuse the singular value filtering, at low-frequency only use simple wiener filter, and finally use anti-wavelettransform to reconstruct the denoising image. Experimental results show that this method is effective in denoising, while it retains the original details.

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更新日期/Last Update: 1900-01-01