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Proceedings Paper

Wavelet-based feature indices as a data mining tool for hyperspectral imagery exploitation
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Paper Abstract

Advances in hyperspectral sensor technology increasingly provide higher resolution and higher quality data for the accurate generation of terrain categorization/classification (TERCAT) maps. The generation of TERCAT maps from hyperspectral imagery can be accomplished using a variety of spectral pattern analysis algorithms; however, the algorithms are sometimes complex, and the training of such algorithms can be tedious. Further, hyperspectral imagery contains a voluminous amount of data with contiguous spectral bands being highly correlated. These highly correlated bands tend to provide redundant information for classification/feature extraction computations. In this paper, we introduce the use of wavelets to generate a set of Generalized Difference Feature Index (GDFI) measures, which transforms a hyperspectral image cube into a derived set of GDFI bands. A commonly known special case of the proposed GDFI approach is the Normalized Difference Vegetation Index (NDVI) measure, which seeks to emphasize vegetation in a scene. Numerous other band-ratio measures that emphasize other specific ground features can be shown to be a special case of the proposed GDFI approach. Generating a set of GDFI bands is fast and simple. However, the number of possible bands is capacious and only a few of these “generalized ratios” will be useful. Judicious data mining of the large set of GDFI bands produces a small subset of GDFI bands designed to extract specific TERCAT features. We extract/classify several terrain features and we compare our results with the results of a more sophisticated neural network feature extraction routine.

Paper Details

Date Published: 2 November 2004
PDF: 12 pages
Proc. SPIE 5558, Applications of Digital Image Processing XXVII, (2 November 2004); doi: 10.1117/12.559510
Show Author Affiliations
Edmundo Simental, U.S. Army Research Engineer and Development Ctr. (United States)
Edward H. Bosch, National Geospatial-Intelligence Agency (United States)
Robert S. Rand, U.S. Army Research Engineer and Development Ctr. (United States)

Published in SPIE Proceedings Vol. 5558:
Applications of Digital Image Processing XXVII
Andrew G. Tescher, Editor(s)

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