Adaptive Image Processing Systems

Abstract

This project is concerned with adaptive image processing systems. In this dissertation I present the ground work for a generalized adaptive image processing (AIP) methodology / environment that can evolve to increasingly complex problems. The generalized image sequence processing environment defined in this research was evaluated by mapping example user image sequence problems through the AIP representation to an instantiation / implementation under the ISIS model integrated computing signal processing platform (SPP) environment. The AIP methodology breaks up adaptive image sequence processing problems into localized control loops. Complex adaptive image sequence processing problems can be broken down utilizing hierarchy or other combinations of the AIP elements. The AIP localized processing loop includes the following top level representations: monitoring point, preprocessor, evaluator, planner, reconfigurer, and user goals. The architecture of these basic building blocks allows for their growth/evolution to increasingly sophisticated implementations.