CLASSIFICATION OF POLARIMETRIC SAR IMAGES BASED ON COMBINING SUPPORT VECTOR MACHINE CLASSIFIER AND MARKOV RANDOM FIELDS

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MASJEDI ALI; MAGHSOUDI YASSER; VALADAN ZOEJ MOHAMAD JAVAD

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Journal: ENGINEERING JOURNAL OF GEOSPATIAL INFORMATION TECHNOLOGY Year:2016 | Volume:3 | Issue:4 Page(s): 0-0

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Title

CLASSIFICATION OF POLARIMETRIC SAR IMAGES BASED ON COMBINING SUPPORT VECTOR MACHINE CLASSIFIER AND MARKOV RANDOM FIELDS

Author(s)

MASJEDI ALI | MAGHSOUDI YASSER | VALADAN ZOEJ MOHAMAD JAVAD | Issue Writer Certificate

Keywords

MARKOV RANDOM FIELDSQ2

SUPPORT VECTOR MACHINEQ1

CONTEXTUAL IMAGE CLASSIFICATIONQ2

SPATIAL INFORMATIONQ2

Abstract

Recent studies show that image classification techniques which use both spectral and SPATIAL INFORMATION are more suitable, effective, and robust than those that use only spectral information. Although late model SUPPORT VECTOR MACHINEs (SVMs) have been providing accurate results in the studies, this method is intrinsically non-contextual, which represents significant limitation in image classification. In this paper, we propose a rigorous framework which integrates SVMs and Markov random field models in a unique formulation for spatial contextual classification of various species of forest trees, ground vegetation, and water using polar metric synthetic aperture radar data. Genetic algorithm is employed for selecting appropriate features and automatic estimation of optimal parameters. Comparison of the accuracy of the proposed method with baseline methods was performed. Comparison of the accuracy of the proposed method with some other methods was carried out. The results show that this algorithm allowed approximately 19%, 14%, 11%, 5% and 3% increase in overall accuracy with respect to the Wishart, WMRF, SVM, aMRF and MSVC methods, respectively.

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APA: Copy

MASJEDI, ALI, MAGHSOUDI, YASSER, & VALADAN ZOEJ, MOHAMAD JAVAD. (2016). CLASSIFICATION OF POLARIMETRIC SAR IMAGES BASED ON COMBINING SUPPORT VECTOR MACHINE CLASSIFIER AND MARKOV RANDOM FIELDS. ENGINEERING JOURNAL OF GEOSPATIAL INFORMATION TECHNOLOGY, 3(4), 0-0. SID. https://sid.ir/paper/355958/en

Vancouver: Copy

MASJEDI ALI, MAGHSOUDI YASSER, VALADAN ZOEJ MOHAMAD JAVAD. CLASSIFICATION OF POLARIMETRIC SAR IMAGES BASED ON COMBINING SUPPORT VECTOR MACHINE CLASSIFIER AND MARKOV RANDOM FIELDS. ENGINEERING JOURNAL OF GEOSPATIAL INFORMATION TECHNOLOGY[Internet]. 2016;3(4):0-0. Available from: https://sid.ir/paper/355958/en

IEEE: Copy

ALI MASJEDI, YASSER MAGHSOUDI, and MOHAMAD JAVAD VALADAN ZOEJ, “CLASSIFICATION OF POLARIMETRIC SAR IMAGES BASED ON COMBINING SUPPORT VECTOR MACHINE CLASSIFIER AND MARKOV RANDOM FIELDS,” ENGINEERING JOURNAL OF GEOSPATIAL INFORMATION TECHNOLOGY, vol. 3, no. 4, pp. 0–0, 2016, [Online]. Available: https://sid.ir/paper/355958/en

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