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26 April 2007 SPICE: a sparsity promoting iterated constrained endmember extraction algorithm with applications to landmine detection from hyperspectral imagery
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Abstract
An extension of the Iterated Constrained Endmembers (ICE) algorithm that incorporates sparsity promoting priors to find the correct number of endmembers is presented. In addition to solving for endmembers and endmember fractional maps, this algorithm attempts to autonomously determine the number of endmembers required for a particular scene. The number of endmembers is found by adding a sparsity-promoting term to ICE's objective function. This method is applied to long wave infrared, LWIR, hyperspectral data to seek out vegetation endmembers and define a vegetation mask for the reduction of false alarms in landmine data.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Alina Zare and Paul Gader "SPICE: a sparsity promoting iterated constrained endmember extraction algorithm with applications to landmine detection from hyperspectral imagery", Proc. SPIE 6553, Detection and Remediation Technologies for Mines and Minelike Targets XII, 655319 (26 April 2007); https://doi.org/10.1117/12.722595
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