Object detection in hyperspectral imagery using normalized cross spectrum energy

M. I. Elbakary; M. S. Alam

doi:10.1117/12.833486

1 September 2009 Object detection in hyperspectral imagery using normalized cross spectrum energy

M. I. Elbakary, M. S. Alam

Proceedings Volume 7442, Optics and Photonics for Information Processing III; 74421G (2009) https://doi.org/10.1117/12.833486
Event: SPIE Optical Engineering + Applications, 2009, San Diego, California, United States

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.

Citation Download Citation

M. I. Elbakary and M. S. Alam "Object detection in hyperspectral imagery using normalized cross spectrum energy", Proc. SPIE 7442, Optics and Photonics for Information Processing III, 74421G (1 September 2009); https://doi.org/10.1117/12.833486

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