Comparison of using single- or multi-polarimetric TerraSAR-X images for segmentation and classification of man-made maritime objects
Lorenzo Bruzzone (Hrsg.), Image and Signal Processing for Remote Sensing XVII, Proceedings of SPIE Vol. 8180, 2011.
SPIE Remote Sensing: Image and Signal Processing for Remote Sensing XVII, Prag, 19.-22. September 2011
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.