Unmixing method for hyperspectral data based on sub-space method with learning process-Reference-Cited by-同舟云学术

Unmixing method for hyperspectral data based on sub-space method with learning process

Published:2009-08 Issue:4 Volume:44 Page:517-523
ISSN:0273-1177
Container-title:Advances in Space Research
language:en
Short-container-title:Advances in Space Research

Author:

Arai Kohei,Chen Huahui

Publisher

Elsevier BV

Subject

Space and Planetary Science,Aerospace Engineering,General Earth and Planetary Sciences,Atmospheric Science,Geophysics,Astronomy and Astrophysics

Reference20 articles.

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3. Label relaxation using a linear mixture model;Arai;Int. J. Remote Sens.,1992

4. Adaptive least square method for estimation of partial cloud coverage within a pixel;Arai;Int. J. Remote Sens.,1995

5. Arai, K., Inagaki, R. Nonlinear mixel model taking into account multiple reflections between ground cover targets and the atmosphere, in: Proceedings of the 33rd General Conference of Remote Sensing Society of Japan, 2002.

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1. An Unsupervised Binary and Multiple Change Detection Approach for Hyperspectral Imagery Based on Spectral Unmixing;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2019-12

2. Development of a Network-Based Method for Unmixing of Hyperspectral Data;IEEE Transactions on Geoscience and Remote Sensing;2012-03