摘要
云雾是遥感图像获取与应用时的常见噪声。因小波变换具有较好的时频分析特性,被广泛地应用于遥感图像的去云处理中。随着小波分析理论与技术的发展,出现了许多种形式小波变换,从云雾图像的频域特性出发,利用不同的小波变换方法对遥感图像进行了去云实验。结果表明,能完成整数到整数变换的提升小波更适用于遥感图像的去云处理。
Cloud and mist are common noise in remote sensing data capture and application.With good time-frequency analysis features,wavelet transformations are widely used in haze removing of remote sensing images.With the development of wavelet theory,there have been many forms of wavelet transforms.Based on the frequency features of cloud and mist images,this paper presents comparative experiments of applying different wavelet transformations to remove noise.The results indicate that the lifting wavelet transformation which can complete integer to integer transformation is more suitable for cloud reduction of remote sensing imagaery.
出处
《信息工程大学学报》
2011年第6期708-712,共5页
Journal of Information Engineering University
基金
国家863计划资助项目(2009AA121403)
关键词
小波变换
遥感图像
云雾去除
同态滤波
wavelet transformation
remote sensing image
cloud removing
homographic filtering
