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Proceedings Paper

A sub-pixel based method to extract and interpret information from image and its preliminary application
Author(s): Hui Li; Yunpeng Wang; Yang Cao; Xingfang Wang
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Paper Abstract

Resolving sub-pixel area information extraction has gained increasing attention in the remote sensing community. Automated morphological endmember extraction (AMEE) which integrates spatial and spectral information to select endmembers, is able to provide a relatively good characterization of general landscape conditions. As tradition support vector machine (SVM) predicts only class label, in order to obtain the abundance fractions of targets of interest, SVM method can be combined with pairwise coupling. This paper describes a model which combines SVM approach and AMEE algorithm. One of the main advantages of using this model is that it performs automatic sub-pixel information detection. At last, simulated and real Landsat TM data are used to demonstrate the potential of this approach.

Paper Details

Date Published: 7 November 2008
PDF: 8 pages
Proc. SPIE 7147, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Classification of Remote Sensing Images, 71470N (7 November 2008); doi: 10.1117/12.813224
Show Author Affiliations
Hui Li, Guangzhou Institute of Geochemistry (China)
South China Normal Univ. (China)
Yunpeng Wang, Guangzhou Institute of Geochemistry (China)
Yang Cao, South China Normal Univ. (China)
Xingfang Wang, Guangzhou Institute of Geochemistry (China)
South China Normal Univ. (China)


Published in SPIE Proceedings Vol. 7147:
Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Classification of Remote Sensing Images

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