Hyper-spectral image processing applications on the SIMD Pixel Processor for the digital battlefield

Sek M. Chai, Antonio Gentile, Wilfredo E. Lugo-Beauchamp, José L. Cruz-Rivera, D. Scott Wills

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

Future military scenarios will rely on advanced imaging sensor technology beyond the visible spectrum to gain total battlefield awareness. Real-time processing of these data streams requires tremendous computational workloads and I/O throughputs. This paper presents three applications for hyper-spectral data streams, vector quantization, region autofocus, and K-means clustering, on the SIMD Pixel Processor (SIMPil). In SIMPil, an image sensor array (focal plane) is integrated on top of a SIMD computing layer to provide direct coupling between sensors and processors, alleviating I/O bandwidth bottlenecks while maintaining low power consumption and portability. Simulation results with sustained operation throughputs of 500-1500 Gops/sec support real-time performance and promote focal plane processing on SIMPil.

Original languageEnglish (US)
Title of host publicationProceedings - IEEE Workshop on Computer Vision Beyond the Visible Spectrum
Subtitle of host publicationMethods and Applications, CVBVS 1999
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages130-138
Number of pages9
ISBN (Electronic)0769500501, 9780769500508
DOIs
StatePublished - 1999
Externally publishedYes
Event1st IEEE Workshop on Computer Vision Beyond the Visible Spectrum: Methods and Applications, CVBVS 1999 - Fort Collins, United States
Duration: Jun 21 1999Jun 22 1999

Publication series

NameProceedings - IEEE Workshop on Computer Vision Beyond the Visible Spectrum: Methods and Applications, CVBVS 1999

Conference

Conference1st IEEE Workshop on Computer Vision Beyond the Visible Spectrum: Methods and Applications, CVBVS 1999
Country/TerritoryUnited States
CityFort Collins
Period6/21/996/22/99

ASJC Scopus subject areas

  • Instrumentation
  • Computer Vision and Pattern Recognition
  • Signal Processing

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