GPU Implementation of an Automatic Target Detection and Classification Algorithm for Hyperspectral Image Analysis

@article{Bernab2013GPUIO,
  title={GPU Implementation of an Automatic Target Detection and Classification Algorithm for Hyperspectral Image Analysis},
  author={Sergio Bernab{\'e} and Sebasti{\'a}n L{\'o}pez and Antonio J. Plaza and Roberto Sarmiento},
  journal={IEEE Geoscience and Remote Sensing Letters},
  year={2013},
  volume={10},
  pages={221-225}
}
The detection of (moving or static) targets in remotely sensed hyperspectral images often requires real-time responses for swift decisions that depend upon high computing performance of algorithm analysis. The automatic target detection and classification algorithm (ATDCA) has been widely used for this purpose. In this letter, we develop several optimizations for accelerating the computational performance of ATDCA. The first one focuses on the use of the Gram-Schmidt orthogonalization method… CONTINUE READING
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