Feature Extraction And Classification Of Oil Spills In Sar Imagery
نویسنده
چکیده
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 lookalikes. 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.
منابع مشابه
Dark Spot Detection from SAR Intensity Imagery with Spatial Density Thresholding for Oil Spill Monitoring
I hereby declare that I am the sole author of this thesis. This is a true copy of the thesis, including any required final revisions, as accepted by my examiners. I understand that my thesis may be made electronically available to the public. Abstract Since the 1980s, satellite-borne synthetic aperture radar (SAR) has been investigated for early warning and monitoring of marine oil spills to pe...
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