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Proceedings Paper

Illumination-invariant recognition of 3D hyperspectral textures using spectral/spatial Gabor filters
Author(s): Tien C. Bau; Glenn Healey
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Paper Abstract

We develop a method for the recognition of textures with three-dimensional structure in hyperspectral images. Properties of a texture are captured by a feature vector that is generated by a bank of spectral/spatial Gabor filters. Variation in the illumination and atmospheric conditions is modeled using a subspace of the feature vectors. Since a large bank of filters is used, we develop methods for reducing the dimension of the feature vector that is used to represent a texture. The goal of the dimension-reduction process is to optimize the discriminability of a set of textures. We demonstrate the utility of the approach using experiments with hyperspectral textures of three-dimensional objects that are generated by DIRSIG over a range of conditions.

Paper Details

Date Published: 13 May 2010
PDF: 11 pages
Proc. SPIE 7695, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVI, 76950F (13 May 2010); doi: 10.1117/12.850774
Show Author Affiliations
Tien C. Bau, Univ. of California, Irvine (United States)
Glenn Healey, Univ. of California, Irvine (United States)


Published in SPIE Proceedings Vol. 7695:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVI
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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