Interpretation of remotely sensed images in a context of multisensor fusion using a multispecialist architecture

A scene interpretation system is presented in a multisensor fusion context the application of which involves the interpretation of remote sensed images. The authors discuss how multisensor fusion is achieved, and derive the modeling problems for objects, scene, and strategy. The proposed multispecialist architecture takes into account the knowledge about sensors, the multiple viewing notion (shot), and the uncertainty and imprecision of models and data modeled with possibility theory. Generic models of objects are represented by concepts independent of sensors. Three kinds of specialists are present in the architecture: generic specialists (scene and conflict), semantic object specialists, and low level specialists. A blackboard structure with a centralized control is used. The interpreted scene is implemented as a matrix of pointers allowing easy conflict detection and spatial context verification. An interpretation system for SAR/SPOT sensor images is described, and an example of a scene interpretation is shown