2011 · 13 citations · 3 references
ComputingComputer ScienceOcean EngineeringComputer VisionMachine VisionRemote SensingDigital Image ProcessingObject RecognitionOptical Ocean SensorsRemote Sensing Image AnalysisRemote Sensing ImagerySatellite SensorsComputation SpeedGraph-based SegmentationRemote Sensing SegmentationSatellite Image AnalysisShipborne Remote SensingVessel Monitoring Systems
Automatic detection and recognition of ship in satellite images is very important and has a wide array of applications. This paper concentrates on optical satellite sensor, which provides an important approach for ship monitoring. Graph-based fore/background segmentation scheme is used to extract ship candidant from optical satellite image chip after the detection step, from course to fine. Shadows on the ship are extracted in a CFAR scheme. Because all the parameters in the graph-based algorithms and CFAR are adaptively determined by the algorithms, no parameter tuning problem exists in our method. Experiments based on measured optical satellite images shows our method achieved good balance between computation speed and ship extraction accuracy.
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Level Set Evolution without Re-Initialization: A New Variational Formulation
Chunming Li, Chenyang Xu, Changfeng Gui et al. · 2005 · 1.8K citations