A genetic algorithm for combining new and existing image processing tools for multispectral imagery.

被引:14
作者
Brumby, SP [1 ]
Harvey, NR [1 ]
Perkins, S [1 ]
Porter, RB [1 ]
Szymanski, JJ [1 ]
Theiler, J [1 ]
Bloch, JJ [1 ]
机构
[1] Los Alamos Natl Lab, Los Alamos, NM 87545 USA
来源
ALGORITHMS FOR MULTISPECTRAL, HYPERSPECTRAL, AND ULTRASPECTRAL IMAGERY VI | 2000年 / 4049卷
关键词
evolutionary computation; genetic algorithms; image processing; remote sensing; multispectral imagery; hyperspectral imagery;
D O I
10.1117/12.410371
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
We describe the implementation and performance of a genetic algorithm (GA) which evolves and combines image processing tools for multispectral imagery (MSI) datasets. Existing algorithms for particular features can also be "re-tuned" and combined with the newly evolved image processing tools to rapidly produce customized feature extraction tools. First results from our software system were presented previously. We now report on work extending our system to look for a range of broad-area features in MSI datasets. These features demand an integrated spatiospectral approach, which our system is designed to use. We describe our chromosomal representation of candidate image processing algorithms, and discuss our set of image operators. Our application has been geospatial feature extraction using publicly available MSI and hyperspectral imagery (HSI). We demonstrate our system on NASA/Jet Propulsion Laboratory's Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) HSI which has been processed to simulate MSI data from the Department of Energy's Multispectral Thermal Imager (MTI) instrument. We exhibit some of our evolved algorithms, and discuss their operation and performance.
引用
收藏
页码:480 / 490
页数:11
相关论文
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