Abstract:
The objective of the research is to study the usability of Compact Polarimetry mode CTLR and evaluate the potential in improving the accuracy of the ship detection algorithms covering wider swath with reasonable degree of False Alarm (FA). The research limits use of SAR (RISAT-1 CFRS & MRS data, Sentinel 1A GRDH & IW data) and software tools, such as, ERDAS Imagine, Matlab and Exelis ENVI for analysis. The observation of maritime activity is the need of time which has improved since inception of Synthetic Aperture Radar (SAR) imagery from space and aerial platforms. However the large amounts of modern SAR systems image data generate are capable of quickly overburdening a human observer. Conventionally EO image interpretation is done manually is accurate but has got limitations of high processing cost & time besides being in-efficient in adverse weather conditions like fog or clouding. However Microwave SAR remote sensing offers cost-effectiveness with better efficiency and flexibility for the identification of ship under all weather conditions. This research has taken the problem of ship detection and aimed to solve it using advanced computational techniques. The research also discusses techniques which can be adapted for better visualization and classification of image in systematic coverage for ship detection which both Sentinel-1A & Risat-1 has been analysed.
