Effect Analysis of UFCLS Linear Spectral Mixture Analysis Method on Classification of Remote Sensing Images

LUO Hongxia; GONG Jianya

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Volume 29 Issue 7

Jul. 2004

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Geomatics and Information Science of Wuhan University > 2004 > 29(7): 615-618.

LUO Hongxia, GONG Jianya. Effect Analysis of UFCLS Linear Spectral Mixture Analysis Method on Classification of Remote Sensing Images[J]. Geomatics and Information Science of Wuhan University, 2004, 29(7): 615-618.

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Effect Analysis of UFCLS Linear Spectral Mixture Analysis Method on Classification of Remote Sensing Images

LUO Hongxia^1,2,
GONG Jianya¹

1 State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 129 Luoyu Road, Wuhan 430079, China;
2 School of Resource and Environment, Southwest Normal University, 2 Tiansheng Road, Chongqing 400715, China

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Received Date: April 07, 2004
Published Date: July 04, 2004

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The abundance fractions of endmembers in an image pixel are estimated by unsupervised fully constrained least squares (UFCLS) based on the inversion of linear spectral mixture method. The results of the experiment show that the effects are good. Compared to CSMA method, UFCLS method is better in both the effects of classification and the consumption of computation time.
- classification of remote sensing image,
- linear spectral mixture model,
- least square

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Effect Analysis of UFCLS Linear Spectral Mixture Analysis Method on Classification of Remote Sensing Images

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