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Proceedings Paper

Evolving retrieval algorithms with a genetic programming scheme
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Paper Abstract

The retrieval of scene properties (surface temperature, material type, vegetation health, etc.) from remotely sensed data is the ultimate goal of many earth observing satellites. The algorithms that have been developed for these retrievals are informed by physical models of how the raw data were generated. This includes models of radiation as emitted and/or reflected by the scene, propagated through the atmosphere, collected by the optics, detected by the sensor, and digitized by the electronics. To some extent, the retrieval is the inverse of this 'forward' modeling problem. But in contrast to this forward modeling, the practical task of making inferences about the original scene usually requires some ad hoc assumptions, good physical intuition, and a healthy dose of trial and error. The standard MTI data processing pipeline will employ algorithms developed with this traditional approach. But we will discuss some preliminary research on the use of a genetic programming scheme to 'evolve' retrieval algorithms. Such a scheme cannot compete with the physical intuition of a remote sensing scientist, but it may be able to automate some of the trial and error. In this scenario, a training set is used, which consists of multispectral image data and the associated 'ground truth;' that is, a registered map of the desired retrieval quantity. The genetic programming scheme attempts to combine a core set of image processing primitives to produce an IDL (Interactive Data Language) program which estimates this retrieval quantity from the raw data.

Paper Details

Date Published: 27 October 1999
PDF: 10 pages
Proc. SPIE 3753, Imaging Spectrometry V, (27 October 1999); doi: 10.1117/12.366303
Show Author Affiliations
James P. Theiler, Los Alamos National Lab. (United States)
Neal R. Harvey, Los Alamos National Lab. (United States)
Steven P. Brumby, Los Alamos National Lab. (United States)
John J. Szymanski, Los Alamos National Lab. (United States)
Steve Alferink, Los Alamos National Lab. (United States)
Simon J. Perkins, Los Alamos National Lab. (United States)
Reid B. Porter, Los Alamos National Lab. (United States)
Jeffrey J. Bloch, Los Alamos National Lab. (United States)

Published in SPIE Proceedings Vol. 3753:
Imaging Spectrometry V
Michael R. Descour; Sylvia S. Shen, Editor(s)

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