Virtual Experts for Imagery Registration and Conflation

Abstract. The unique human expertise in imagery analysis should be preserved and shared with other imagery analysts to improve image analysis and decision-making. Such knowledge can serve as a corporate memory and be a base for an imagery virtual expert. The core problem in reaching this goal is constructing a methodology and tools that can assist in building the knowledge base of imagery analysis. This paper provides a framework for an imagery virtual expert system that supports imagery registration and conflation tasks. The approach involves two strategies: (1) recording expertise onthe-fly and (2) extracting information from the expert system in an optimized way. The second strategy is based on the theory of monotone Boolean functions