Paper
12 May 2010 Spectrally-invariant synthetic discriminant signature for hyperspectral target detection using spectral fringe-adjusted joint transform correlation
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Abstract
A practical challenge that designers of hyperspectral (HS) target detection algorithms must confront is the variety of spectral sampling properties exhibited by various HS imaging sensors. Examples of these variations include different spectral resolutions and the possibility of regular or irregular sampling. To confront this problem, we propose construction of a spectral synthetic discriminant signature (SSDS). The SSDS is constructed from q spectral training signatures which are obtained by sampling the original target signature. Since the SSDS is formulated offline, it does not impose any burden on the processing speed of the recognition process. Results on our HS scenery show that use of the SSDS in conjunction with the spectral fringe-adjusted joint transform correlation (SFJTC) algorithm provides spectrallyinvariant target detection, yielding area under ROC curve (AUROC) values above 0.993.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Aed El-Saba, Adel A. Sakla, and Wesam A. Sakla "Spectrally-invariant synthetic discriminant signature for hyperspectral target detection using spectral fringe-adjusted joint transform correlation", Proc. SPIE 7696, Automatic Target Recognition XX; Acquisition, Tracking, Pointing, and Laser Systems Technologies XXIV; and Optical Pattern Recognition XXI, 76961T (12 May 2010); https://doi.org/10.1117/12.850520
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Cited by 1 scholarly publication.
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KEYWORDS
Target detection

Detection and tracking algorithms

Sensors

Joint transforms

Hyperspectral target detection

Reflectivity

Automatic target recognition

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