Target detection with multiple reflection linear unmixing for hyperspectral remote sensing imagery

Hsuan Ren, Shih Min Hsu, Chiu Yu Liu

研究成果: 書貢獻/報告類型會議論文篇章同行評審

摘要

Linear mixture model has been widely used for abundance estimation in remotely sensed imagery. Since each pixel in the remote sensing images usually covers several meters on the ground and contains more than one material, its spectrum can be considered as a mixture of all the materials residents in that pixel. Linear mixture model simply assumes this mixture is linear and then estimates the abundance fraction by least square approaches. If the surface is smooth, linear mixture can approximately fit the spectrum. However, if the surface is rough, the multiple reflection effect needs to be considered. In this study, we propose a multiple reflection linear mixture which not only consider single reflection linear mixture, but also includes double and triple reflections. In the model, we also adopt one single factor for the probability of multiple reflections or the roughness. The preliminary result shows the multiple reflection linear mixture can fit the spectrum with less error comparing to traditional linear mixture assumption.

原文???core.languages.en_GB???
主出版物標題33rd Asian Conference on Remote Sensing 2012, ACRS 2012
頁面1461-1464
頁數4
出版狀態已出版 - 2012
事件33rd Asian Conference on Remote Sensing 2012, ACRS 2012 - Pattaya, Thailand
持續時間: 26 11月 201230 11月 2012

出版系列

名字33rd Asian Conference on Remote Sensing 2012, ACRS 2012
2

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???event.eventtypes.event.conference???33rd Asian Conference on Remote Sensing 2012, ACRS 2012
國家/地區Thailand
城市Pattaya
期間26/11/1230/11/12

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