PRESENTING A FEATURE SELECTION METHOD BASED ON GENETIC ALGORITHM AND DECISION TREE FOR CLASSIFYING FULLY POLARIMETRIC SAR IMAGES

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KHOSRAVI IMAN; MOUSAVI MIR MAJID; AMINI JALAL

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Journal: ENGINEERING JOURNAL OF GEOSPATIAL INFORMATION TECHNOLOGY Year:2015 | Volume:3 | Issue:2 Page(s): 75-88

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Title

PRESENTING A FEATURE SELECTION METHOD BASED ON GENETIC ALGORITHM AND DECISION TREE FOR CLASSIFYING FULLY POLARIMETRIC SAR IMAGES

Author(s)

KHOSRAVI IMAN | MOUSAVI MIR MAJID | AMINI JALAL | Issue Writer Certificate

Keywords

REGIONAL GRAVITY FIELD MODELINGQ1

SPHERICAL RADIAL BASIS FUNCTIONSQ2

GENETIC ALGORITHMQ2

TIKHONOV ALGORITHMQ2

Abstract

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.

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APA: Copy

KHOSRAVI, IMAN, MOUSAVI, MIR MAJID, & AMINI, JALAL. (2015). PRESENTING A FEATURE SELECTION METHOD BASED ON GENETIC ALGORITHM AND DECISION TREE FOR CLASSIFYING FULLY POLARIMETRIC SAR IMAGES. ENGINEERING JOURNAL OF GEOSPATIAL INFORMATION TECHNOLOGY, 3(2), 75-88. SID. https://sid.ir/paper/230115/en

Vancouver: Copy

KHOSRAVI IMAN, MOUSAVI MIR MAJID, AMINI JALAL. PRESENTING A FEATURE SELECTION METHOD BASED ON GENETIC ALGORITHM AND DECISION TREE FOR CLASSIFYING FULLY POLARIMETRIC SAR IMAGES. ENGINEERING JOURNAL OF GEOSPATIAL INFORMATION TECHNOLOGY[Internet]. 2015;3(2):75-88. Available from: https://sid.ir/paper/230115/en

IEEE: Copy

IMAN KHOSRAVI, MIR MAJID MOUSAVI, and JALAL AMINI, “PRESENTING A FEATURE SELECTION METHOD BASED ON GENETIC ALGORITHM AND DECISION TREE FOR CLASSIFYING FULLY POLARIMETRIC SAR IMAGES,” ENGINEERING JOURNAL OF GEOSPATIAL INFORMATION TECHNOLOGY, vol. 3, no. 2, pp. 75–88, 2015, [Online]. Available: https://sid.ir/paper/230115/en

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