Application of BS-GEP algorithm in Remote sensing Image classification

  • dan Lin dan Lin
Keywords: Remote Sensing image classification, Gene expression programming, local convergence, classification rules, Clas Sification accuracy

Abstract

I It is difficult for the Traditional statistical Remote sensing classification algorithm to get higher
Classifica tion accuracy under the condition of complex state. To solve this problem, BS-GEP algorithm is
introduced to the study of remote Sensing image classification Problemsin this paper, to Avoid local
converge NCE of the algorithm caused by the population diversity, the characteristic o f the traditional GEP, and
solve the problem of getting higher classification Accuracy difficultly under the complex condition state. The
experimental results have shown that classification rules based on the BS-GEP classifier can is converted into
Mathema Tical expressions and obtain higher classification accuracy. Compared with GEP algorithm, the
confused degreeof theclassification results are ivelyLow,and compared with maximum likelihood algorithm, the
classification results are relatively clear. The classification accuracy of the classifier has been reached to.

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