• Title/Summary/Keyword: Constrained Linear Spectral Unmixing(CLSU)

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Unsupervised Endmember Selection Optimization Process based on Constrained Linear Spectral Unmixing of Hyperion Image (Hyperion 영상의 제약선형분광혼합분석 기반 무감독 Endmember 추출 최적화 기법)

  • Choi Jae-Wan;Kim Yong-Il;Yu Ki-Yun
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • 2006.04a
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    • pp.211-216
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    • 2006

  • The Constrained Linear Spectral Unmixing(CLSU) is investigated for sub-pixel image processing, Its result is the abundance map which mean fractions of endmember existing in a mixed pixel. Compared to the Linear Spectral Unmixing using least square method, CLSU uses the NNLS (Non-Negative Least Square) algorithm to guarantee that the estimated fractions are constrained. But, CLSU gets Into difficulty in image processing due to select endmember at a user's disposition. In this study, endmember selection optimization method using entropy in the error-image analysis is proposed. In experiments which is used hyperion image, it is shown that our method can select endmember number than CLSU based on unsupervised endemeber selection.

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