Virtual Experts for Imagery Registration and Conflation

Abstract

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