%0 Conference Paper %1 szymanski02feature %A Szymanski, John J. %A Brumby, Steven P. %A Pope, Paul %A Eads, Damian %A Esch-Mosher, Diana %A Galassi, Mark %A Harvey, Neal R. %A McCulloch, Hersey D. W. %A Perkins, Simon J. %A Porter, Reid %A Theiler, James %A Young, A. Cody %A Bloch, Jeffrey J. %A David, Nancy %B Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery VIII %D 2002 %E Shen, Sylvia S. %E Lewis, Paul E. %K algorithms, genetic programming %P 338--345 %T Feature extraction from multiple data sources using genetic programming %U http://citeseer.ist.psu.edu/540967.html %V 4725 %X Feature extraction from imagery is an important and long-standing problem in remote sensing. In this paper, we report on work using genetic programming to perform feature extraction simultaneously from multispectral and digital elevation model (DEM) data. We use the GENetic Imagery Exploitation (GENIE) software for this purpose, which produces image-processing software that inherently combines spatial and spectral processing. GENIE is particularly useful in exploratory studies of imagery, such as one often does in combining data from multiple sources. The user trains the software by painting the feature of interest with a simple graphical user interface. GENIE then uses genetic programming techniques to produce an image-processing pipeline. Here, we demonstrate evolution of image processing algorithms that extract a range of land cover features including towns, wildfire burnscars, and forest. We use imagery from the DOE/NNSA Multispectral Thermal Imager (MTI) spacecraft, fused with USGS 1:24000 scale DEM data.

@inproceedings{szymanski02feature, abstract = {Feature extraction from imagery is an important and long-standing problem in remote sensing. In this paper, we report on work using genetic programming to perform feature extraction simultaneously from multispectral and digital elevation model (DEM) data. We use the GENetic Imagery Exploitation (GENIE) software for this purpose, which produces image-processing software that inherently combines spatial and spectral processing. GENIE is particularly useful in exploratory studies of imagery, such as one often does in combining data from multiple sources. The user trains the software by painting the feature of interest with a simple graphical user interface. GENIE then uses genetic programming techniques to produce an image-processing pipeline. Here, we demonstrate evolution of image processing algorithms that extract a range of land cover features including towns, wildfire burnscars, and forest. We use imagery from the DOE/NNSA Multispectral Thermal Imager (MTI) spacecraft, fused with USGS 1:24000 scale DEM data.}, added-at = {2008-06-19T17:46:40.000+0200}, author = {Szymanski, John J. and Brumby, Steven P. and Pope, Paul and Eads, Damian and Esch-Mosher, Diana and Galassi, Mark and Harvey, Neal R. and McCulloch, Hersey D. W. and Perkins, Simon J. and Porter, Reid and Theiler, James and Young, A. Cody and Bloch, Jeffrey J. and David, Nancy}, biburl = {https://www.bibsonomy.org/bibtex/249e6ad1068af57c348cd910d1be5b974/brazovayeye}, booktitle = {Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery VIII}, editor = {Shen, Sylvia S. and Lewis, Paul E.}, interhash = {f888322694ade6877bd44bb6e6473aaa}, intrahash = {49e6ad1068af57c348cd910d1be5b974}, keywords = {algorithms, genetic programming}, month = {August}, notes = {also appears as oai:CiteSeerPSU:540967 but given different authors!}, organisation = {SPIE--The International Society for Optical Engineering}, pages = {338--345}, series = {SPIE}, size = {8 pages}, timestamp = {2008-06-19T17:52:31.000+0200}, title = {Feature extraction from multiple data sources using genetic programming}, url = {http://citeseer.ist.psu.edu/540967.html}, volume = 4725, year = 2002 }