Parallel evolution of image processing tools for multispectral imagery

Neal R. Harvey, Steven P. Brumby, Simon J. Perkins, Reid B. Porter, James Theiler, A. Cody Young, John J. Szymanski, Jeffrey J. Bloch

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

11 Citations (Scopus)

Abstract

We describe the implementation and performance of a parallel, hybrid evolutionary-algorithm-based system, which optimizes image processing tools for feature-finding tasks in multi-spectral imagery (MSI) data sets. Our system uses an integrated spatio-spectral approach and is capable of combining suitably-registered data from different sensors. We investigate the speed-up obtained by parallelization of the evolutionary process via multiple processors (a workstation cluster) and develop a model for prediction of run-times for different numbers of processors. We demonstrate our system on Landsat Thematic Mapper MSI, covering the recent Cerro Grande fire at Los Alamos, NM, USA.

Original languageEnglish (US)
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
PublisherSociety of Photo-Optical Instrumentation Engineers
Pages72-82
Number of pages11
Volume4132
DOIs
StatePublished - 2000
Externally publishedYes
EventImaging Spectrometry VI - San Diego, USA
Duration: Jul 31 2000Aug 2 2000

Other

OtherImaging Spectrometry VI
CitySan Diego, USA
Period7/31/008/2/00

Fingerprint

Evolutionary algorithms
imagery
image processing
central processing units
Fires
Image processing
thematic mappers (LANDSAT)
workstations
Sensors
coverings
sensors
predictions

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Condensed Matter Physics

Cite this

Harvey, N. R., Brumby, S. P., Perkins, S. J., Porter, R. B., Theiler, J., Young, A. C., ... Bloch, J. J. (2000). Parallel evolution of image processing tools for multispectral imagery. In Proceedings of SPIE - The International Society for Optical Engineering (Vol. 4132, pp. 72-82). Society of Photo-Optical Instrumentation Engineers. https://doi.org/10.1117/12.406611

Parallel evolution of image processing tools for multispectral imagery. / Harvey, Neal R.; Brumby, Steven P.; Perkins, Simon J.; Porter, Reid B.; Theiler, James; Young, A. Cody; Szymanski, John J.; Bloch, Jeffrey J.

Proceedings of SPIE - The International Society for Optical Engineering. Vol. 4132 Society of Photo-Optical Instrumentation Engineers, 2000. p. 72-82.

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

Harvey, NR, Brumby, SP, Perkins, SJ, Porter, RB, Theiler, J, Young, AC, Szymanski, JJ & Bloch, JJ 2000, Parallel evolution of image processing tools for multispectral imagery. in Proceedings of SPIE - The International Society for Optical Engineering. vol. 4132, Society of Photo-Optical Instrumentation Engineers, pp. 72-82, Imaging Spectrometry VI, San Diego, USA, 7/31/00. https://doi.org/10.1117/12.406611
Harvey NR, Brumby SP, Perkins SJ, Porter RB, Theiler J, Young AC et al. Parallel evolution of image processing tools for multispectral imagery. In Proceedings of SPIE - The International Society for Optical Engineering. Vol. 4132. Society of Photo-Optical Instrumentation Engineers. 2000. p. 72-82 https://doi.org/10.1117/12.406611
Harvey, Neal R. ; Brumby, Steven P. ; Perkins, Simon J. ; Porter, Reid B. ; Theiler, James ; Young, A. Cody ; Szymanski, John J. ; Bloch, Jeffrey J. / Parallel evolution of image processing tools for multispectral imagery. Proceedings of SPIE - The International Society for Optical Engineering. Vol. 4132 Society of Photo-Optical Instrumentation Engineers, 2000. pp. 72-82
@inproceedings{aee880b4e9914284a426a1c44570053f,
title = "Parallel evolution of image processing tools for multispectral imagery",
abstract = "We describe the implementation and performance of a parallel, hybrid evolutionary-algorithm-based system, which optimizes image processing tools for feature-finding tasks in multi-spectral imagery (MSI) data sets. Our system uses an integrated spatio-spectral approach and is capable of combining suitably-registered data from different sensors. We investigate the speed-up obtained by parallelization of the evolutionary process via multiple processors (a workstation cluster) and develop a model for prediction of run-times for different numbers of processors. We demonstrate our system on Landsat Thematic Mapper MSI, covering the recent Cerro Grande fire at Los Alamos, NM, USA.",
author = "Harvey, {Neal R.} and Brumby, {Steven P.} and Perkins, {Simon J.} and Porter, {Reid B.} and James Theiler and Young, {A. Cody} and Szymanski, {John J.} and Bloch, {Jeffrey J.}",
year = "2000",
doi = "10.1117/12.406611",
language = "English (US)",
volume = "4132",
pages = "72--82",
booktitle = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "Society of Photo-Optical Instrumentation Engineers",

}

TY - GEN

T1 - Parallel evolution of image processing tools for multispectral imagery

AU - Harvey, Neal R.

AU - Brumby, Steven P.

AU - Perkins, Simon J.

AU - Porter, Reid B.

AU - Theiler, James

AU - Young, A. Cody

AU - Szymanski, John J.

AU - Bloch, Jeffrey J.

PY - 2000

Y1 - 2000

N2 - We describe the implementation and performance of a parallel, hybrid evolutionary-algorithm-based system, which optimizes image processing tools for feature-finding tasks in multi-spectral imagery (MSI) data sets. Our system uses an integrated spatio-spectral approach and is capable of combining suitably-registered data from different sensors. We investigate the speed-up obtained by parallelization of the evolutionary process via multiple processors (a workstation cluster) and develop a model for prediction of run-times for different numbers of processors. We demonstrate our system on Landsat Thematic Mapper MSI, covering the recent Cerro Grande fire at Los Alamos, NM, USA.

AB - We describe the implementation and performance of a parallel, hybrid evolutionary-algorithm-based system, which optimizes image processing tools for feature-finding tasks in multi-spectral imagery (MSI) data sets. Our system uses an integrated spatio-spectral approach and is capable of combining suitably-registered data from different sensors. We investigate the speed-up obtained by parallelization of the evolutionary process via multiple processors (a workstation cluster) and develop a model for prediction of run-times for different numbers of processors. We demonstrate our system on Landsat Thematic Mapper MSI, covering the recent Cerro Grande fire at Los Alamos, NM, USA.

UR - http://www.scopus.com/inward/record.url?scp=0034504362&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0034504362&partnerID=8YFLogxK

U2 - 10.1117/12.406611

DO - 10.1117/12.406611

M3 - Conference contribution

AN - SCOPUS:0034504362

VL - 4132

SP - 72

EP - 82

BT - Proceedings of SPIE - The International Society for Optical Engineering

PB - Society of Photo-Optical Instrumentation Engineers

ER -