多孔小波和非下采样滤波器组去除遥感图像的多种噪声

上海交通大学学报（自然版） ›› 2012, Vol. 46 ›› Issue (02): 233-238.

• 自动化技术、计算机技术 • 上一篇下一篇

多孔小波和非下采样滤波器组去除遥感图像的多种噪声

徐华楠，刘哲，刘灿

(西北工业大学理学院，西安 710072)

出版日期:2012-02-28 发布日期:2012-02-28
基金资助:
国家自然科学基金项目 (61071170)，新世纪优秀人才支持计划资助项目

Remote Sensing Image Denoising by àtrous Wavelet and Nonsubsampled Directional Filter Bank

XU Hua-Nan, LIU Zhe, LIU Can

(School of Science, Northwestern Polytechnical University, Xian 710072, China)

Online:2012-02-28 Published:2012-02-28

摘要/Abstract

摘要： 结合àtrous小波变换和非下采样轮廓波变换的优点,提出一种基于àtrous非下采样轮廓波变换的遥感图像去噪方法.该方法用非抽取离散小波变换的àtrous算法对图像进行多尺度分解,然后用非下采样的多方向滤波器组对得到的细节分量进行多方向分解.对含有多种噪声的遥感图像,àtrous非下采样轮廓波变换将图像中不同种类的噪声分解到不同的小波系数分量中,使得可以根据噪声特性选择最合适的去噪方法,比用一种方法去除所有类型的噪声更科学且去噪效果更好.

关键词: 遥感图像, à, trous小波, 非下采样轮廓波变换, 图像去噪

Abstract: This paper proposed a method of denoising the remote sensing image based on àtrousnonsubsampled contourlet transform. The method uses the àtrous wavelet—an undecimated discrete wavelet transform algorithm to decompose the image into two parts possessing approximate part and detail parts, which are the same size as the original image. Then the nonsubsampled directional filter bank is employed to decompose the detail parts into directional subbands. The different kinds of noises of the remote sensing image can be decomposed into the wavelet coefficients in different scale and directions, with which the best method can be chosen based on the characteristics of the different noises. It is more scientific and more effective than just using one method for all kinds of noises in the past. It is proved that the method proposed in the paper is more useful in removing the noise of the image, reserving richer fine textures and edge information than other traditional filtering methods.

Key words: remote sensing image； à, trous wavelet； nonsubsampled contourlet； image denoising

中图分类号:

TP 391

徐华楠, 刘哲, 刘灿. 多孔小波和非下采样滤波器组去除遥感图像的多种噪声[J]. 上海交通大学学报（自然版）, 2012, 46(02): 233-238.

XU Hua-Nan, LIU Zhe, LIU Can. Remote Sensing Image Denoising by àtrous Wavelet and Nonsubsampled Directional Filter Bank[J]. Journal of Shanghai Jiaotong University, 2012, 46(02): 233-238.

参考文献

［1］罗丽,袁真,王珂.基于àtrouscontourlet变换的遥感图像融合算法［J］.模式识别与人工智能， 2007, 20(2) :248253.
LUO Li, YUAN Zhen, WANG Ke. A remote sensing image fusion algorithm based on àtrouscontourlet transformation ［J］.PR&AI, 2007, 20(2) :248253.
［2］Do M N, Vetterli M. Contourlets: A directional multiresolution image representation［C］//IEEE International Conference on Image Processing (ICIP). Rochester: IEEE Press, 2002: 357360.
［3］郭旭静,王祖林.基于尺度间相关的非下采样Contourlet图像降噪算法［J］.光电子·激光，2007,18(9):11161119.
GUO Xujing, WANG Zulin. Nonsubsampled contourlet image denoising based on interscale correlations［J］. Journal of Optoelectronics ·Laser, 2007,18(9):11161119.
［4］Da Cunha A L, Zhou Jianping, Do M N. Nonsubsampled contourlet transform: Filter design and applications in denoising［C］//IEEE International Conference on Image Processing. Genoa, Italy: IEEE Press, 2005: 749752.
［5］Chibani Y, Houscine A. The joint use of HIS transform and redundant wavelet decomposition for fusing multispectral and panchromatic images［J］. INT J Remote Sensing, 2002,23(18):38213833.
［6］Hoschneider M, kronlandMartinet R, Morlet J， et al. A realtime algorithm for signal analysis with the help of the wavelet transform［C］//Proceedings of the International Conference on Wavelet (IPTI). Berlin: SpringerVerlag, 1989:286297.
［7］张晓东,李德仁,蔡东翔,等. àtrous小波分解在边缘检测中的应用［J］.武汉大学学报：信息科学版， 2001, 26(1):2933.
ZHANG Xiaodong, LI Deren, CAI Dongxiang, et al. àtrous wavelet decomposition applied to detecting image edge［J］.

Geomatics and Information Science of Wuhan University, 2001, 26(1):2933.
［8］王连庆,安锦文.基于无下采样小波Contourlet变换的图像融合算法［J］.激光与红外, 2008, 38(2):191194.
WANG Lianqing, AN Jinwen. Image fusion based on nonsubsampled waveletcontourlet transform［J］. Laser&Infrared, 2008, 38(2):191194.
［9］Po D D Y, Do M N. Directional multiscale statistical modeling of images ［C］//SPIE Conference on Wavelet Applications in Signal and Image Processing. San Diego, USA: IEEE Press,2003: 6979.
［10］Xu Y, Weaver B, Healy D, et al. Wavelet transform domain filters: A spatially selective noise filtration technique ［J］. IEEE Trans on Image Processing, 1994, 3(6) :747758.
［11］郁梅,易文娟,蒋刚毅.基于Contourlet变换尺度间相关的图像去噪［J］.光电工程，2006,33(6):7377.
YU Mei, YI Wenjuan, JIANG Gangyi. Image denoise based on interscale correlations of contourlet transform ［J］. OptoElectronic Engineering, 2006,33(6):7377.
［12］Mallat S G. A wavelet tour of signal processing［M］. Second Edition. London: Academic Press, 1999.
［13］Mallat S G. A theory for multiresolution signal decomposition: The wavelet representation ［J］. IEEE Transaction on Pattern Analysis and Machine Intelligence, 1989, 11(7): 674693.
［14］Donoho D L. Denosing by softthresholding［J］. IEEE Transactions on Information Theory, 1995, 41(3):613627.

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多孔小波和非下采样滤波器组去除遥感图像的多种噪声

Remote Sensing Image Denoising by àtrous Wavelet and Nonsubsampled Directional Filter Bank

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