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Proceedings Paper

Object detection in hyperspectral imagery using normalized cross spectrum energy
Author(s): M. I. Elbakary; M. S. Alam
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Paper Abstract

Hyperspectral sensors can facilitate automatic pattern recognition in cluttered imagery since man made objects often differ considerably from the natural background in absorbing and reflecting the radiation at various wavelengths i.e., the identification of the objects is based on spectral signature of the objects in the scene. Normalized cross spectrum (cross-phase spectrum) has been extensively used for image registration. In this paper, we introduce preliminary results for a new approach for object detection in hyperspectral imagery by employing normalized cross spectrum. Normalized cross spectrum is employed as similarity measure between the spectral signature of known object and the investigated spectral signatures in the data. The new algorithm uses the advantages of the shape of the peak of the correlation to detect the pattern of interest. The proposed algorithm has been tested using real life hyperspectral imagery and the results show the effectiveness of the proposed approach.

Paper Details

Date Published: 1 September 2009
PDF: 7 pages
Proc. SPIE 7442, Optics and Photonics for Information Processing III, 74421G (1 September 2009); doi: 10.1117/12.833486
Show Author Affiliations
M. I. Elbakary, Univ. of South Alabama (United States)
M. S. Alam, Univ. of South Alabama (United States)


Published in SPIE Proceedings Vol. 7442:
Optics and Photonics for Information Processing III
Khan M. Iftekharuddin; Abdul Ahad Sami Awwal, Editor(s)

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