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A study of fuzzy clustering within the IGSCR framework

Published: 28 March 2008 Publication History

Abstract

The iterative guided spectral class rejection (IGSCR) classification algorithm uses an underlying clustering method and a decision rule to arrive at final classifications for remotely sensed data. Previous versions of IGSCR have used a hard clustering method such as k-means or ISODATA. In an effort to ultimately create a fuzzy version of IGSCR, this work uses an underlying fuzzy clustering algorithm within the IGSCR framework to study the effects of using the fuzzy clustering algorithm. IGSCR with fuzzy k-means was applied to a Landsat ETM+ satellite image to produce a two class classification (forest and nonforest), and results show that although fuzzy k-means did not lead to increased accuracy, the classification results are dramatically different for IGSCR using traditional k-means and fuzzy k-means.

References

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Jensen, J. R., Ramsey, E. W., Mackey Jr., H. E., Christensen, E. J., and Shartz, R. R. 1987. Inland wetland change detection using aircraft MSS data. Photogrammetric Engineering & Remote Sensing. 53 (5), 521--529.
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Musy, R. F., Wynne, R. H., Blinn, C. E., Scrivani, J. A., and McRoberts, R. E. 2006. Automated Forest Area Estimation via Iterative Guided Spectral Class Rejection. Photogrammetric Engineering & Remote Sensing. 72 (8), 949--960.
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  • (2008)A Fuzzy Homogeneity Test for the Iterative Guided Spectral Class Rejection AlgorithmIGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium10.1109/IGARSS.2008.4779136(II-883-II-886)Online publication date: Jul-2008

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ACMSE '08: Proceedings of the 46th annual ACM Southeast Conference
March 2008
548 pages
ISBN:9781605581057
DOI:10.1145/1593105
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

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Published: 28 March 2008

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ACM SE08
ACM SE08: ACM Southeast Regional Conference
March 28 - 29, 2008
Alabama, Auburn

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Overall Acceptance Rate 502 of 1,023 submissions, 49%

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  • (2008)A Fuzzy Homogeneity Test for the Iterative Guided Spectral Class Rejection AlgorithmIGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium10.1109/IGARSS.2008.4779136(II-883-II-886)Online publication date: Jul-2008

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