Supervised band selection for optimal use of data from airborne hyperspectral sensors


Riedmann, M. and Milton, E.J. (2003) Supervised band selection for optimal use of data from airborne hyperspectral sensors. In, IGARSS '03 Proceedings of the International Geoscience and Remote Sensing Symposium, 21-25 July 2003, Toulouse, France. Proceedings of the International Geoscience and Remote Sensing Symposium (IGARSS) New York, Institute of Electrical and Electronics Engineers (IEEE), 1770-1772.

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Description/Abstract

This paper presents a practical supervised band selection procedure for airborne imaging spectrometers and Maximum Likelihood classification (MLC) as data application. The output band set is optimal in band location, width and number regarding the MLC accuracy of the classification task.
The supervised algorithm is based on feature selection and requires a user-defined class set. For two given semi-natural vegetation data and class sets, the selected band sets performed superior to established vegetation band sets used in current
satellite and airborne sensors, most noticeably for the first few bands. The algorithm was implemented in IDLTM/ENVITM. It may also be used for feature selection, the generation of classdiscriminate colour composites, the prioritization of already
existing band sets, and the determination of the intrinsic discriminant dimensionality of the data set.

Item Type: Book Section
Additional Information: CD-ROM
Related URLs:
Subjects: G Geography. Anthropology. Recreation > G Geography (General)
Divisions: University Structure - Pre August 2011 > School of Geography > Remote Sensing and Spatial Analysis
ePrint ID: 6175
Date Deposited: 21 May 2004
Last Modified: 27 Mar 2014 18:00
URI: http://eprints.soton.ac.uk/id/eprint/6175

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