A multi-specialist architecture for sensor fusion in remote sensing

Presents a scene interpretation architecture in the context of multi-sensor fusion. This architecture is based on blackboard and multi-specialist concepts, and offers knowledge representation capabilities to express knowledge about an application in an explicit way. Knowledge description includes the characteristics of the sensors, and a semantic object description independent of the sensor characteristics. The detection strategy is based on the fundamental notion of spatial context linking the objects of the scene, and the notion of salient object. An interpretation is a semantic model of the real observed scene, including object location, object characteristics and relations between objects. This architecture has a highly modular structure allowing easy incorporation of new knowledge, and new specialists. To demonstrate the reliability of the approach, an application of SAR/SPOT data fusion developed with this architecture is briefly presented, and the results of an interpretation session are shown