文章基本信息

标题：The Efficacy of Semi-Automatic Classification Result by Using Different Cloud Detection and Diminution Method
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作者：C. Y. Hau ; C. H. Liu ; T. Y. Chou 等
期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2008
卷号：XXXVII-B8
页码：607-612
出版社：Copernicus Publications
摘要：Passive Remote Sensing is multi-spectral, rapid and high resolution, but it is very easily influenced by intended to the atmosphere conditions, such as fog and haze. In the past, there have been many studies removed the noise of cloud and haze. This study proposes to use the differences between five filtering methods to judge the differences between their efficiencies. Fast Fourier transforms are used in all five methods to remove clouds. All five methods apply the high-pass filter concept. Standard reference data are used as a basis for companion. The results show that there is a trade-off between classification and appearance; high amounts of information smoothing worsen classification accuracy but improve appearance
关键词：Image processing; Change detection; Image understanding; Matching; Air quality