Reconnaissance of extended targets in SAR image data

Screening and thematic data exploitation are important tasks in the reconnaissance cycle. To reduce the work load of the image analysts, an automatization of these tasks is required. For an automatic image exploitation structural image analysis algorithms were developed for multisensor data. The approach is based on the primitive objects line which are generated by appropriate edge detectors. For preprocessing in SAR images, i.e. the change from the iconic to the symbolic level, not only speckle noise prejudices automatic segmentation but also multiple scattering of hard targets in the scene. Several different approaches to filter speckle noise and to detect edges prior to structural image analysis have been investigated. The structural analysis of complex scenes uses the blackboard-based production system (BPI) as framework. The primitive objects are built up step by step applying the productions. For an IMINT report the image data has to be referenced to a cartographic grid. In an automated reconnaissance cycle an automatic image-to-map registration is required. The necessary control points must be detected in the image data and a correspondence between map and image control points must be found. The transformation parameters can then be calculated. Additionally, when using map information, expectation areas can be defined and processing needs can be reduced efficiently.