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Proceedings Paper

Three-dimensional hyperspectral texture recognition using multiband correlation models
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Paper Abstract

We develop new algorithms based on multiband correlation models for the recognition of hyperspectral textures in three dimensions. The dependence of the observed texture of a material sample on viewing and illumination angles can have varying degrees of complexity. The bidirectional texture function (BTF) describes the appearance of a textured surface as a function of the illumination and viewing directions. The lack of appropriate hyperspectral image sets has limited attempts to characterize the BTF for 3D hyperspectral textures. In this paper, we use the DIRSIG model to generate a set of hyperspectral images over ranges of illumination and viewing angles in the 0.4 to 2.5 spectral region. We evaluate the performance of our methods for recognizing three-dimensional hyperspectral textures under unknown illumination angle.

Paper Details

Date Published: 23 September 2003
PDF: 8 pages
Proc. SPIE 5093, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery IX, (23 September 2003); doi: 10.1117/12.488560
Show Author Affiliations
Miaohong Shi, Univ. of California, Irvine (United States)
Glenn E. Healey, Univ. of California, Irvine (United States)


Published in SPIE Proceedings Vol. 5093:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery IX
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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