Classification of Synthetic Aperture Radar Images


  • Devang Maheta ME Student, Electronics & Communication Department, G. H. Patel College of Engineering &Technology,VallabhVidyanagar, Gujarat


SAR (Synthetic Aperture Radar), feature extraction, POLSARPRO, fully polarimetric, wishart classification


In current research, classification of SAR (Synthetic Aperture Radar) image technology is being used to
monitor agriculture field, forest, and terrain analysis, is one of the fastest growing fields in image processing. To analyze
the information included in SAR images, robust and efficient classification algorithms are required. The intent is to
explore the application of information obtained from fully polarimetric data for land cover classification. Various land
cover classification techniques are available in the literature, but still uncertainty exists in labeling various clusters to
their own classes without using any a priori information. Therefore, the present work is focused on analyzing useful
intrinsic information extracted from SAR observables.The classification approach has been evaluated for ALOS
PALSAR, Radarsat data. Here, supervised wishart classification and H/A/Alpha decomposition methods are used for
classification. POLSARPRO_v5.0 toolbox is used for this purpose.



How to Cite

Devang Maheta. (2015). Classification of Synthetic Aperture Radar Images. International Journal of Advance Engineering and Research Development (IJAERD), 2(7), 224–228. Retrieved from