Genetic programming approach to extracting features from remotely sensed imagery

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{Brumby:2001:FUSION,
  author =       "Steven P. Brumby and James Theiler and 
                 Simon Perkins and Neal R. Harvey and John J. Szymanski",
  title =        "Genetic programming approach to extracting features
                 from remotely sensed imagery",
  booktitle =    "FUSION 2001: Fourth International Conference on Image
                 Fusion",
  year =         "2001",
  address =      "Montreal, Quebec, Canada",
  month =        "7-10 " # aug,
  email =        "brumby@lanl.gov",
  keywords =     "genetic algorithms, genetic programming, Evolutionary
                 Computation, Image Processing, Remote Sensing,
                 Multispectral Imagery, Panchromatic imagery",
  URL =          "http://public.lanl.gov/perkins/webdocs/brumbyFUSION2001.pdf",
  size =         "8 pages",
  abstract =     "Multi-instrument data sets present an interesting
                 challenge to feature extraction algorithm developers.
                 Beyond the immediate problems of spatial
                 co-registration, the remote sensing scientist must
                 explore a complex algorithm space in which both spatial
                 and spectral signatures may be required to identify a
                 feature of interest. We describe a genetic
                 programming/supervised classifier software system,
                 called Genie, which evolves and combines
                 spatio-spectral image processing tools for remotely
                 sensed imagery. We describe our representation of
                 candidate image processing pipelines, and discuss our
                 set of primitive image operators. Our primary
                 application has been in the field of geospatial feature
                 extraction, including wildfire scars and general
                 land-cover classes, using publicly available
                 multi-spectral imagery (MSI) and hyper-spectral imagery
                 (HSI). Here, we demonstrate our system on Landsat 7
                 Enhanced Thematic Mapper (ETM+) MSI. We exhibit an
                 evolved pipeline, and discuss its operation and
                 performance.",
  notes =        "oai:CiteSeerPSU:567526 seems to be wrong",
}

Genetic Programming entries for Steven P Brumby James Theiler Simon Perkins Neal R Harvey John J Szymanski

Citations