Feature Extraction and Classification of Oil Spills in SAR Imagery
Synthetic Aperture RADAR (SAR) imaging system is used to monitor the marine system. Oil spill pollution plays a significant role in damaging marine ecosystem. One main advantages of SAR is that it can generate imagery under all weather conditions. In a SAR image dark spots can be generated by number of phenomena. The dark spots may be of algae, low wind areas, coastal areas and oil spills. The detected dark spots are then classified based on the features. The features of dark spot are extracted to discriminate oil spill from look-alikes. The textural and statistical features are extracted and analyzed for oil spill identification. This paper discusses about the different feature extraction and classification method for oil spill detection and their preliminary results.
Keywords: oil spill, SAR, features, detection, classification, look-alikes.
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ABOUT THE AUTHORS
Radhika V
Prof & HOD, Computer science department, Sri krishna Arts and Science college Kuniamuthur, coimbatore, Tamil nadu, India
G.Padmavathi
Prof & Head, Department of Computer Science Avinashilingam University for Women, Coimbatore-641 043,India.
Radhika V
Prof & HOD, Computer science department, Sri krishna Arts and Science college Kuniamuthur, coimbatore, Tamil nadu, India
G.Padmavathi
Prof & Head, Department of Computer Science Avinashilingam University for Women, Coimbatore-641 043,India.
