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一种基于小波变换去除遥感图像噪声的方法
引用本文:侯波,迟耀斌,朱重光,赵忠明.一种基于小波变换去除遥感图像噪声的方法[J].遥感学报,2003,7(5):379-385.
作者姓名:侯波  迟耀斌  朱重光  赵忠明
作者单位:1. 北京遥感信息研究所,北京,100011;中国科学院遥感应用研究所,北京,100101
2. 中国科学院遥感应用研究所,北京,100101
摘    要:采用小波系数极大值跟踪法去除图像噪声,建立了尺度间小波系数极大值跟踪矩阵,标识出小波系数极大值的信噪属性,剔除了噪声部分对应小波系数极大值,从而抑制了噪声污染。与常规去噪方法相比,该方法不仅有效地去除了噪声,同时保持了图像边沿细节,具有良好的消除噪声效果。

关 键 词:噪声  图像质量  小波变换  极大值  Kpschitz指数  奇异性
文章编号:1007-4619(2003)05-0379-07
收稿时间:2/8/2002 12:00:00 AM
修稿时间:2002年2月8日

Remote Sensing Image Denoising in the Wavelet Domain
HOU Bo,CHI Yao-bin,ZHU Chong-guang and ZHAO Zhong-ming.Remote Sensing Image Denoising in the Wavelet Domain[J].Journal of Remote Sensing,2003,7(5):379-385.
Authors:HOU Bo  CHI Yao-bin  ZHU Chong-guang and ZHAO Zhong-ming
Abstract:In this paper, we propose a new denoising method, which distinguishes the coefficients' extremums belonging either or to image to noise by the tracking matrixes of the extremums in wavelet domain. The coefficients' extremums that belong to image have transmission property from coarse to fine scale, but the coefficients' extremums that belong to noise do not have. We evaluate the tracking marixes of the extremums different number base on the transmission property of each extremums from coarse to fine scale. The tracking matrixes of the extremums express the different transmission property. By the tracking matrixes of the extremums, we differentiate the wavelet coefficients' extremums and then remove the coefficients' extremums belonging to noise. Experimental results show that the denoising proposed in this paper is effective both in reserving the edge and in removing noise.
Keywords:Wavelet transformation  Extremum  Lipschitz exponent  Singular points
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