Genetic Programming as a Preprocessing Tool to Aid Multi-Temporal Imagery Classification
Created by W.Langdon from
gp-bibliography.bib Revision:1.7964
- @InProceedings{Momm:2006:ASPRS,
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author = "Henrique Momm and Greg Easson and Dawn Wilkins",
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title = "Genetic Programming as a Preprocessing Tool to Aid
Multi-Temporal Imagery Classification",
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booktitle = "Proceedings of the ASPRS 2006 Annual Conference",
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year = "2006",
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editor = "Alan Mikuni and George Hepner",
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address = "Reno, Nevada, USA",
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month = "15-" # may,
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organization = "American Society for Photogrammetry and Remote
Sensing",
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keywords = "genetic algorithms, genetic programming, remote
sensing",
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URL = "http://www.asprs.org/a/publications/proceedings/reno2006/0101.pdf",
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size = "11 pages",
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abstract = "Classification-based applications of remotely sensed
data have increased significantly over the years. Very
often, these data are gathered from different sources
and in different formats causing the classification
process to be scene specific. Alternatively, spectral
band indices have been developed to emphasise some
elements based on spectral characteristics and
therefore improving the final classification accuracy.
This research applies a multi-disciplinary approach in
which genetic programming (GP) and standard
unsupervised algorithms are integrated into a single
iterative process to develop spectral indices for each
element being investigated (such as water, impervious
surfaces, dense vegetation, etc). A set of indices
formed by mathematical and logical operations of the
spectral bands are evolved using genetic operations.
The application of non-linear indices enhances the
relative spectral difference among the elements
investigated improving the clustering capability of the
data. The algorithm's ability to generalise provides an
alternative to classify multi-temporal data with a
single methodology. An example application is given for
the water and impervious surface delineation using
Landsat MSS, Landsat TM, and Landsat ETM+ imagery.
Initial results are comparable to more labour intensive
scene-specific supervised classification.",
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notes = "http://www.asprs.org/conference-archive/reno2006/final-prog.htm",
- }
Genetic Programming entries for
Henrique G Momm
Greg Easson
Dawn Wilkins
Citations