15 November 2000 Parallel evolution of image processing tools for multispectral imagery
Author Affiliations +
Proceedings Volume 4132, Imaging Spectrometry VI; (2000); doi: 10.1117/12.406611
Event: International Symposium on Optical Science and Technology, 2000, San Diego, CA, United States
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.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Neal R. Harvey, Steven P. Brumby, Simon J. Perkins, Reid B. Porter, James P. Theiler, Aaron Cody Young, John J. Szymanski, Jeffrey J. Bloch, "Parallel evolution of image processing tools for multispectral imagery", Proc. SPIE 4132, Imaging Spectrometry VI, (15 November 2000); doi: 10.1117/12.406611; https://doi.org/10.1117/12.406611

Image processing

Binary data


Multispectral imaging

Computer architecture

Feature extraction

Time metrology

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