30 October 2012 Classification of visible point sources using hyperspectral chromotomosynthetic imagery
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A hyperspectral chromotomosynthetic imaging (CTI) system is used to detect and classify a collection of 21 scattered, spectrally diverse point-like sources. The instrument operates in the visible to near IR (400 to 800 nm) and has the potential to collect spectral imagery at great than 10 Hz. A two-dimensional wideband spatial image of the target scene is used to detect and spatially characterize the targets leading to optimization of the three-dimensional (3-D) spatial/spectral reconstruction of the hyperspectral image cube. The instrument is assessed by directly comparing results to spatial data collected by a wideband image and hyperspectral data collected using a liquid crystal tunable filter (LCTF). Target classification using k-means clustering of observed spectra yielded 5 to 6 target classes for each methodology, indicating information obtained using CTI was similar to that collected by the LCTF. The wide-band spatial content of the scene reconstructed from the CTI data is of same or better quality in terms of background noise and target intensities as a single frame collected by the undispersed imaging system with projections taken at every 1 deg. Performance is dependent on the number of projections used, with projections at 5 deg producing adequate results in terms of target characterization. The CTI has 2 to 4 times the spectral resolution of the LCTF. The data collected by the CTI system can simultaneously provide spatial information of equal quality as a the bandpass imaging system, provide high-frame rate slitless one-dimensional spectra, and generate 3-D hyperspectral imagery which can be exploited to provide the same results as a traditional multiband spectral imaging system.
© 2012 Society of Photo-Optical Instrumentation Engineers (SPIE)
Randall L. Bostick, Randall L. Bostick, Glen P. Perram, Glen P. Perram, } "Classification of visible point sources using hyperspectral chromotomosynthetic imagery," Journal of Applied Remote Sensing 6(1), 063584 (30 October 2012). https://doi.org/10.1117/1.JRS.6.063584 . Submission:

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