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:: Volume 3, Issue 2 (9-2015) ::
jgit 2015, 3(2): 75-88 Back to browse issues page
Presenting A Feature Selection Method Based On Genetic Algorithm and Decision Tree For Classifying Fully Polarimetric SAR Images
Iman Khosravi *, Mir Majid Mousavi, Jalal Amini
University of Tehran
Abstract:   (4615 Views)

A fully polarimetric synthetic aperture radar (POLSAR) image can provide important polarimetric features for land cover classification. These features can be the parameters obtained from scatering, covariance and coherency matrices, parameters extracted from target decomposition methods or both of them. In this paper, many polarimetric features are extracted from a POLSAR image. Then, with the use of Genetic Algorithm (GA) and Decision Tree (DT), a feature selection method based on the classification is presented. Afterwards, a comparative analysis is accomplished between DT classification with features selected from the proposed method and DT classification with all features. Moreover, the proposed method should be compared with the feature selection method of GA and Support Vector Machine (SVM). The results indicated that the accuracy of the proposed method (DT classification with the features selected from GA-DT algorithm) is nearly 3% higher than the ones of the DT classification with all features and it is approximately equal with the ones of the DT classification with the features selected from GA-SVM algorithm. However, the performance speed of the proposed method is approximately 5 times more than the ones of DT classification with the features selected from GA-SVM algorithm. As an another result, the features selected from the proposed method have a more success than the ones of two other methods at classifying the urban areas and vegetation classes.

Keywords: Regional gravity field modeling, Spherical Radial Basis Functions, Genetic algorithm, Tikhonov algorithm
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Type of Study: Research |
Received: 2016/03/11 | Accepted: 2016/03/11 | Published: 2016/03/11
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Khosravi I, Mousavi M M, Amini J. Presenting A Feature Selection Method Based On Genetic Algorithm and Decision Tree For Classifying Fully Polarimetric SAR Images. jgit. 2015; 3 (2) :75-88
URL: http://jgit.kntu.ac.ir/article-1-232-en.html


Volume 3, Issue 2 (9-2015) Back to browse issues page
نشریه علمی-پژوهشی مهندسی فناوری اطلاعات مکانی Engineering Journal of Geospatial Information Technology
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