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基于小波变换的多波段遥感图像条带噪声的去除
引用本文:陈劲松,朱博勤,邵芸.基于小波变换的多波段遥感图像条带噪声的去除[J].遥感信息,2003(2):6-9.
作者姓名:陈劲松  朱博勤  邵芸
作者单位:中国科学院遥感应用研究所,北京,100101
基金项目:中国科学院知识创新工程重要项目‘数字地球基础理论研究’(KZCXZ-312)
摘    要:介绍了几种在TM,MSS,SPOT等多传感器遥感图像中条带噪声去除方法的特点,提出了一种基于小波变换的条带噪声去除方法,并以几何纠正前的非均匀地物分布的CMODIS图像为实验数据,对这些方法的去条带噪声效果作了比较。结果表明,本提出的方法要优于以前的几种常用方法,具有很好的去条带效果,同时较好地保持了原图像的特征。这种方法在其它多传感器遥感图像的条带噪声去除中也有很强的适用性。

关 键 词:小波变换  多传感器遥感图像  条带噪声  去噪方法  图像处理  矩匹配  信号响应  CCD扫描
文章编号:1000-3177(2003)70-0006-04
修稿时间:2003年2月19日

Destriping Multi-sensor Imagery Based on Wavelet Transform
CHEN Jin-song,ZHU Bo-qin,SHAO Yun.Destriping Multi-sensor Imagery Based on Wavelet Transform[J].Remote Sensing Information,2003(2):6-9.
Authors:CHEN Jin-song  ZHU Bo-qin  SHAO Yun
Abstract:CMODIS contains abundant spectral information with 34 channels in the range from visible to infrared. But sensor to sensor variation within instrument often leads to striping in many channels of CMODIS. The striping noise can distractingly and obstructively affects the interpretation and application of CMODIS data. This paper discusses the method previously used in striping removal of TM, MSS , MOS- B and presnts a new method based on wavelet transform. The application results of the method to non-geometrically corrected CMODIS data and quantitative analysis of the results show that the new method can achieve the better result than the previously used ones and preserve the spectral characteristic of original image . The new method is also applicable in striping removal of other multi-sensor remote sensing data.
Keywords:CCD signal response  moment matching  wavelet transform  destriping
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