Model of human vision to register and fuse video imagery

Modern capture and storage of digital information have given rise to tremendous repositories of data, but the ability to efficiently and effectively use this data has lagged. A prominent example is the generation of video imagery by Unmanned Aerial Vehicles. This imagery currently must be analyzed by a human observer either in real-time or playback mode (dynamic or frame-by-frame). These manpower-intensive activities become increasingly unpalatable as personnel resources shrink, so an automated system is desired that will assist in transforming the large data sets into vastly smaller sets that still retain the pertinent information. We propose a computational vision model based on physiological and behavioral characteristics of the human visual system to perform the registration of multiple video frames, followed by a fusion process that produces a video mosaic preserving the `important' features (those the human observer would deem important) from each individual frame.