Spaceborne SAR imagery offers high capability for wide-ranging maritime surveillance especially in situations, where AIS (Automatic Identification System) data is not available. Therefore, maritime objects have to be detected and optional information such as size, orientation, or object/ship class is desired. In recent research work,1 we proposed a SAR processing chain consisting of pre-processing, detection, segmentation, and classification for single-polarimetric (HH) TerraSAR-X StripMap images to finally assign detection hypotheses to class “clutter”, “non-ship”, “unstructured ship”, or “ship structure 1” (bulk carrier appearance) respectively “ship structure 2” (oil tanker appearance). In this work, we extend the existing processing chain and are now able to handle full-polarimetric (HH, HV, VH, VV) TerraSAR-X data. With the possibility of better noise suppression using the different polarizations, we slightly improve both the segmentation and the classification process. In several experiments we demonstrate the potential benefit for segmentation and classification. Precision of size and orientation estimation as well as correct classification rates are calculated individually for single- and quad-polarization and compared to each other.
Comparison of using single- or multi-polarimetric TerraSAR-X images for segmentation and classification of man-made maritime objects
2011
2011
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Segmentation and classification of man-made maritime objects in TerraSAR-X images
Fraunhofer Publica | 2011
|Characterization of Alpine Glaciers Using Fully-Polarimetric TerraSAR-X Data
British Library Conference Proceedings | 2011
|Ship Speed Retrieval from Single Channel TerraSAR-X Images
British Library Conference Proceedings | 2010
|Polarimetric SAR Tomography with TerraSAR-X by Means of Distributed Compressed Sensing
British Library Conference Proceedings | 2012
|Fraunhofer Publica | 2009
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