Learned fusion operators based on matrix completion
Kelly K. D. Risko, Charles F. Hester · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2011
The efficient and timely management of imagery captured in the battlefield requires methods capable of searching the voluminous databases and extracting highly symbolic concepts. When processing images, a semantic and definition gap exists between machine representations and the user's language. Based on matrix completion techniques, we present a fusion operator that fuses imagery and expert knowledge provided by user inputs during post analysis. Specifically, an information matrix is formed from imagery and a class map as labeled by an expert. From this matrix an image operator is derived for the extraction/prediction of information from future imagery. We will present results using this technique on single mode data.