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Genetic algorithm based feature selection for target detection in SAR images

Authors
Journal
Image and Vision Computing
0262-8856
Publisher
Elsevier
Publication Date
Volume
21
Issue
7
Identifiers
DOI: 10.1016/s0262-8856(03)00057-x
Keywords
  • Atr System
  • Feature Selection
  • Genetic Algorithm
  • Minimum Description Length
  • Target Detection
Disciplines
  • Computer Science
  • Mathematics

Abstract

Abstract A genetic algorithm (GA) approach is presented to select a set of features to discriminate the targets from the natural clutter false alarms in SAR images. Four stages of an automatic target detection system are developed: the rough target detection, feature extraction from the potential target regions, GA based feature selection and the final Bayesian classification. A new fitness function based on minimum description length principle (MDLP) is proposed to drive GA and it is compared with three other fitness functions. Experimental results show that the new fitness function outperforms the other three fitness functions and the GA driven by it selected a good subset of features to discriminate the targets from clutters effectively.

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