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A knowledge representation architecture for remote sensing image understanding systems

Knowledge plays a very important role in remote sensing image understanding. In this paper, we consider various types of knowledge related to remote sensing image understanding, and present a knowledge representation(KR) architecture. Knowledge in the KR architecture is classified into six types, including object knowledge, image knowledge, environment knowledge, algorithm knowledge, task knowledge, and integrated knowledge, which combine knowledge from symbolic representations and computational intelligence. We analysis each knowledge type and its representation, especially task knowledge and integrated knowledge. We employ agents for task knowledge representation, which are able to finish special tasks. Meanwhile, task agents bridge the gap between low-level image processing methods and high-level semantic descriptions. The KR architecture provides the basis of knowledge services for remote sensing image understanding systems.