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13 May 2010 Illumination-invariant recognition of 3D hyperspectral textures using spectral/spatial Gabor filters
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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.
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Tien C. Bau and Glenn Healey "Illumination-invariant recognition of 3D hyperspectral textures using spectral/spatial Gabor filters", Proc. SPIE 7695, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVI, 76950F (13 May 2010); https://doi.org/10.1117/12.850774
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