Wide area site models are useful for delineating regions of interest and assisting in tasks like monitoring and change detection. They are also useful in registering a newly acquired image to an existing one of the same site, or to a map. This paper presents a complete algorithm for building an approximate 2-D wide-area site model from high resolution, polarimetric Synthetic Aperture Radar (SAR) data. A three stage algorithm-involving detection of possible targets, statistical segmentation of the data into homogeneous regions, and validation of segmentation results-is used for this task. Constant False Alarm Rate (CFAR) detectors are used for target detection, while maximum likelihood labeling is used for initial segmentation. Knowledge of the sensor heading and other geometric cues are used to refine the initial segmentation and to extract man-made objects like buildings, and their shadows, as well as roads, from these images.
展开▼
