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Proceedings Paper

Using moment invariants for the registration and recognition of hyperspectral image regions
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Paper Abstract

We show that moment invariants of spectral distributions provide region descriptors that are independent of changes in the illumination and atmospheric conditions. These invariants can be computed efficiently for band subsets of hyperspectral data. Moment invariants have several applications in hyperspectral data processing. They can be used for the registration of image regions acquired at different times and for the transformation of images acquired at different times to a canonical invariant representation for comparison. Moment invariants can also be used for the recognition of image regions under unknown conditions. We demonstrate the properties of moment invariants using hyperspectral images synthesized using DIRSIG.

Paper Details

Date Published: 12 August 2004
PDF: 8 pages
Proc. SPIE 5425, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery X, (12 August 2004); doi: 10.1117/12.542660
Show Author Affiliations
Chia-Yun Kuan, Univ. of California/Irvine (United States)
Glenn E. Healey, Univ. of California/Irvine (United States)


Published in SPIE Proceedings Vol. 5425:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery X
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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