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- W276437190 abstract "ABSTRACT Previous work with the Bobcat 2013 data set 1 showed that spatial-spectral feature extraction on visible to nearinfrared (VNIR) hyperspectral imagery (HSI) led to better target detection and discrimination than spectral-only techniques; however, the aforementioned study could not consider the possible bene ts of the shortwave-infrared (SWIR) portion of the spectrum due to data limitations. In addition, the spatial resolution of theBobcat 2013 imagery was xed at 8cm without exploring lower spatial resolutions. In this work, we evaluatethe tradeo s in spatial and spectral resolution and spectral coverage between for a common set of targets interms of their e ects on spatial-spectral target detection performance. We show that for our spatial-spectraltarget detection scheme and data sets, the adaptive cosine estimator (ACE) applied to S-DAISY and pseudoZernike moment (PZM) spatial-spectral features can distinguish between targets better than ACE applied onlyto the spectral imagery. In particular, S-DAISY operating on bands uniformly selected from the SWIR portionof ProSpecTIR-VS sensor imagery in conjunction with bands closely corresponding to the Airborne Real-timeCueing Hyperspectral Reconnaissance (ARCHER) sensor's VNIR bands (80 total) led to the best overall averageperfomance in both target detection and discrimination.Keywords: hyperspectral imagery, spatial-spectral feature extraction, feature-level fusion, spatial resolution,spectral resolution" @default.
- W276437190 created "2016-06-24" @default.
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- W276437190 date "2015-05-21" @default.
- W276437190 modified "2023-09-23" @default.
- W276437190 title "On the effects of spatial and spectral resolution on spatial-spectral target detection in SHARE 2012 and Bobcat 2013 hyperspectral imagery" @default.
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- W276437190 doi "https://doi.org/10.1117/12.2177503" @default.
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