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Proceedings Paper

Evaluation of the GPU architecture for the implementation of target detection algorithms for hyperspectral imagery
Author(s): Blas Trigueros-Espinosa; Miguel Vélez-Reyes; Nayda G. Santiago-Santiago; Samuel Rosario-Torres
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Paper Abstract

Hyperspectral sensors can collect hundreds of images taken at different narrow and contiguously spaced spectral bands. This high-resolution spectral information can be used to identify materials and objects within the field of view of the sensor by their spectral signature, but this process may be computationally intensive due to the large data sizes generated by the hyperspectral sensors, typically hundreds of megabytes. This can be an important limitation for some applications where the detection process must be performed in real time (surveillance, explosive detection, etc.). In this work, we developed a parallel implementation of three state-ofthe- art target detection algorithms (RX algorithm, matched filter and adaptive matched subspace detector) using a graphics processing unit (GPU) based on the NVIDIA® CUDA™ architecture. In addition, a multi-core CPUbased implementation of each algorithm was developed to be used as a baseline for the speedups estimation. We evaluated the performance of the GPU-based implementations using an NVIDIA ® Tesla® C1060 GPU card, and the detection accuracy of the implemented algorithms was evaluated using a set of phantom images simulating traces of different materials on clothing. We achieved a maximum speedup in the GPU implementations of around 20x over a multicore CPU-based implementation, which suggests that applications for real-time detection of targets in HSI can greatly benefit from the performance of GPUs as processing hardware.

Paper Details

Date Published: 20 May 2011
PDF: 10 pages
Proc. SPIE 8048, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVII, 80480Q (20 May 2011); doi: 10.1117/12.885621
Show Author Affiliations
Blas Trigueros-Espinosa, Univ. de Puerto Rico Mayagüez (United States)
Miguel Vélez-Reyes, Univ. de Puerto Rico Mayagüez (United States)
Nayda G. Santiago-Santiago, Univ. de Puerto Rico Mayagüez (United States)
Samuel Rosario-Torres, Univ. de Puerto Rico Mayagüez (United States)

Published in SPIE Proceedings Vol. 8048:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVII
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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