4 October 2017 Target detection with compressive sensing hyperspectral images
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Abstract
During the past years, several compressive spectral imaging techniques were developed. With these techniques, an optically compressed version of the spectral datacube is captured. Consequently, the information about the object and targets is captured in a lower dimensional space. A question that rises is whether the reduction of the captured space affects the target detection performance. The answer to this question depends on the compressive spectral imaging technique employed. In most compressive spectral imaging techniques, the target detection performance is deteriorated. We show that our recently introduced technique, dubbed Compressive Sensing Miniature Ultra-Spectral Imaging (CSMUSI), yields similar target detection and false detection rates to that of conventional hyperspectral cameras.
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Yaniv Oiknine, Yaniv Oiknine, Daniel Gedalin, Daniel Gedalin, Isaac August, Isaac August, Dan G. Blumberg, Dan G. Blumberg, Stanley R. Rotman, Stanley R. Rotman, Adrian Stern, Adrian Stern, } "Target detection with compressive sensing hyperspectral images", Proc. SPIE 10427, Image and Signal Processing for Remote Sensing XXIII, 104270O (4 October 2017); doi: 10.1117/12.2277186; https://doi.org/10.1117/12.2277186
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