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Proceedings Paper

On the effects of spatial and spectral resolution on spatial-spectral target detection in SHARE 2012 and Bobcat 2013 hyperspectral imagery
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Paper Abstract

Previous work with the Bobcat 2013 data set1 showed that spatial-spectral feature extraction on visible to near infrared (VNIR) hyperspectral imagery (HSI) led to better target detection and discrimination than spectral-only techniques; however, the aforementioned study could not consider the possible benefits of the shortwaveinfrared (SWIR) portion of the spectrum due to data limitations. In addition, the spatial resolution of the Bobcat 2013 imagery was fixed at 8cm without exploring lower spatial resolutions. In this work, we evaluate the tradeoffs in spatial and spectral resolution and spectral coverage between for a common set of targets in terms of their effects on spatial-spectral target detection performance. We show that for our spatial-spectral target detection scheme and data sets, the adaptive cosine estimator (ACE) applied to S-DAISY and pseudo Zernike moment (PZM) spatial-spectral features can distinguish between targets better than ACE applied only to the spectral imagery. In particular, S-DAISY operating on bands uniformly selected from the SWIR portion of ProSpecTIR-VS sensor imagery in conjunction with bands closely corresponding to the Airborne Real-time Cueing Hyperspectral Reconnaissance (ARCHER) sensor's VNIR bands (80 total) led to the best overall average performance in both target detection and discrimination.

Paper Details

Date Published: 21 May 2015
PDF: 11 pages
Proc. SPIE 9472, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXI, 94720J (21 May 2015); doi: 10.1117/12.2177503
Show Author Affiliations
Jason R. Kaufman, Exelis, Inc. (United States)
Ohio Univ. (United States)
Michael T. Eismann, Air Force Research Lab. (United States)
Bradley M. Ratliff, Exelis, Inc. (United States)
Mehmet Celenk, Ohio Univ. (United States)

Published in SPIE Proceedings Vol. 9472:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXI
Miguel Velez-Reyes; Fred A. Kruse, Editor(s)

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