ENSEMBLE CLASSIFICATION OF POLSAR DATA USING A SPARSE REPRESENTATION-BASED CLASSIFIER

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Saleh Reza; FARSI HASAN; Zahiri Seyyed Hamid

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Seminar Paper

Paper Information

Seminar: CONFERENCE OF IRANIAN AEROSPACE SOCIETY
Year:2016 | Issue:15

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Title

ENSEMBLE CLASSIFICATION OF POLSAR DATA USING A SPARSE REPRESENTATION-BASED CLASSIFIER

Author(s)

Saleh Reza | FARSI HASAN | Zahiri Seyyed Hamid | Issue Writer Certificate

Keywords

POLSAR IMAGE

ENSEMBLE CLASSIFICATION

SPARSE REPRESENTATION

NAIVE BAYES RULE

RELIABILITY

Abstract

THE SYNTHETIC APERTURE RADAR (SAR) IS A TYPE OF COHERENT IMAGING RADAR THAT OPERATES IN THE MICROWAVE BAND. A SAR SYSTEM CAN PROVIDE A DAY-OR-NIGHT, ALL-WEATHER MEANS OF REMOTE SENSING AND PRODUCES HIGH-RESOLUTION IMAGES OF THE LAND UNDER THE ILLUMINATION OF RADAR BEAMS. POLARIMETRIC SYNTHETIC APERTURE RADAR (POLSAR) SYSTEM IS AN ADVANCED FORM OF SAR, WHICH FOCUSES ON EMITTING AND RECEIVING FULLY POLARIZED RADAR WAVES TO CHARACTERIZE TARGETS. POLSAR IMAGES PROVIDE SIGNIFICANTLY MORE INFORMATION THAN SINGLE SAR IMAGES, AND AS A CONSEQUENCE POLSAR DATA CAN BE USED TO DISTINGUISH THE SCATTERING OBJECTS AND TO IMPROVE IMAGE CLASSIFICATION MUCH BETTER THAN CONVENTIONAL SAR DATA. SINCE A LARGE NUMBER OF PARAMETERS CAN BE EXTRACTED FROM POLSAR DATA, OPTIMUM FEATURES ARE USED TO FORM FEATURE VECTOR. SPARSE REPRESENTATION AIMS TO APPROXIMATE A TARGET SIGNAL USING A LINEAR COMBINATION OF ELEMENTARY SIGNALS DRAWN FROM A LARGE CANDIDATE SET, WHICH IS CALLED AS DICTIONARY. SPARSE REPRESENTATIONS HAVE THEREFORE INCREASINGLY BECOME RECOGNIZED AS PROVIDING EXTREMELY HIGH PERFORMANCE FOR DIVERSE APPLICATIONS. IN THIS PAPER, WE USED THIS APPROACH AS A CLASSIFIER. ON THE OTHER HAND, ACCORDING TO RECENT RESEARCH RESULTS, ENSEMBLE CLASSIFIER AS AN EFFECTIVE APPROACH HAS MORE CAPABILITIES COMPARE TO SINGLE-CLASSIFIERS. IT BUILDS AN ENSEMBLE OF WEAK CLASSIFIERS AND COMBINES THE DECISIONS OF THESE WEAK CLASSIFIERS TO ARRIVE AT THE FINAL DECISION. IN THIS PAPER USING A SPARSE REPRESENTATION-BASED CLASSIFIER AND OTHER DIVERSE SINGLE-CLASSIFIERS AN ENSEMBLE OF CLASSIFIERS IS PROPOSED. WE USED NAÏVE BAYES RULE TO COMBINE THE OUTPUTS OF INDIVIDUAL CLASSIFIERS. THE EXPERIMENTS OVER A BENCHMARK POLSAR IMAGE DEMONSTRATE THE EFFECTIVENESS OF THE PROPOSED ALGORITHM IN TERMS OF ACCURACY AND RELIABILITY OVER THE EXISTING TECHNIQUES.

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APA: Copy

Saleh, Reza, FARSI, HASAN, & Zahiri, Seyyed Hamid. (2016). ENSEMBLE CLASSIFICATION OF POLSAR DATA USING A SPARSE REPRESENTATION-BASED CLASSIFIER. CONFERENCE OF IRANIAN AEROSPACE SOCIETY. SID. https://sid.ir/paper/947966/en

Vancouver: Copy

Saleh Reza, FARSI HASAN, Zahiri Seyyed Hamid. ENSEMBLE CLASSIFICATION OF POLSAR DATA USING A SPARSE REPRESENTATION-BASED CLASSIFIER. 2016. Available from: https://sid.ir/paper/947966/en

IEEE: Copy

Reza Saleh, HASAN FARSI, and Seyyed Hamid Zahiri, “ENSEMBLE CLASSIFICATION OF POLSAR DATA USING A SPARSE REPRESENTATION-BASED CLASSIFIER,” presented at the CONFERENCE OF IRANIAN AEROSPACE SOCIETY. 2016, [Online]. Available: https://sid.ir/paper/947966/en

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