Mixed-pixel classification for hyperspectral images based on multichannel singular spectrum analysis

Cheng Tan Tung; Din Chang Tseng; Yeou Long Tsai

Mixed-pixel classification for hyperspectral images based on multichannel singular spectrum analysis

Cheng Tan Tung, Din Chang Tseng, Yeou Long Tsai

資訊工程學系

研究成果: 會議貢獻類型 › 會議論文 › 同行評審

摘要

In this paper, a spectral unmixing technique based on multichannel singular spectrum analysis (MSSA) is applied to derive quantitative information about general land-cover types whose spectra can be determined from the image. The proposed approach can tolerate white noise in the linear model; moreover, we also provide an automatic mechanism to eliminate the undesired singular values as many as possible to get better results. Several experiments for hyperspectral images were conducted to validate the spectral unmixing procedure. Comparisons with the LSOSP approach were also given.

原文	???core.languages.en_GB???
頁面	2370-2372
頁數	3
出版狀態	已出版 - 2001
事件	2001 International Geoscience and Remote Sensing Symposium (IGARSS 2001) - Sydney, NSW, Australia 持續時間: 9 7月 2001 → 13 7月 2001

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???event.eventtypes.event.conference???	2001 International Geoscience and Remote Sensing Symposium (IGARSS 2001)
國家/地區	Australia
城市	Sydney, NSW
期間	9/07/01 → 13/07/01

引用此

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title = "Mixed-pixel classification for hyperspectral images based on multichannel singular spectrum analysis",

abstract = "In this paper, a spectral unmixing technique based on multichannel singular spectrum analysis (MSSA) is applied to derive quantitative information about general land-cover types whose spectra can be determined from the image. The proposed approach can tolerate white noise in the linear model; moreover, we also provide an automatic mechanism to eliminate the undesired singular values as many as possible to get better results. Several experiments for hyperspectral images were conducted to validate the spectral unmixing procedure. Comparisons with the LSOSP approach were also given.",

author = "Tung, {Cheng Tan} and Tseng, {Din Chang} and Tsai, {Yeou Long}",

year = "2001",

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AU - Tung, Cheng Tan

AU - Tseng, Din Chang

AU - Tsai, Yeou Long

PY - 2001

Y1 - 2001

N2 - In this paper, a spectral unmixing technique based on multichannel singular spectrum analysis (MSSA) is applied to derive quantitative information about general land-cover types whose spectra can be determined from the image. The proposed approach can tolerate white noise in the linear model; moreover, we also provide an automatic mechanism to eliminate the undesired singular values as many as possible to get better results. Several experiments for hyperspectral images were conducted to validate the spectral unmixing procedure. Comparisons with the LSOSP approach were also given.

AB - In this paper, a spectral unmixing technique based on multichannel singular spectrum analysis (MSSA) is applied to derive quantitative information about general land-cover types whose spectra can be determined from the image. The proposed approach can tolerate white noise in the linear model; moreover, we also provide an automatic mechanism to eliminate the undesired singular values as many as possible to get better results. Several experiments for hyperspectral images were conducted to validate the spectral unmixing procedure. Comparisons with the LSOSP approach were also given.

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M3 - 會議論文

AN - SCOPUS:0035572223

SP - 2370

EP - 2372

T2 - 2001 International Geoscience and Remote Sensing Symposium (IGARSS 2001)

Y2 - 9 July 2001 through 13 July 2001

ER -

Mixed-pixel classification for hyperspectral images based on multichannel singular spectrum analysis

摘要

???event.eventtypes.event.conference???

指紋

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