Reconfigurable Multi-Spectral Image Processing Architecture



C. Wolinski, F. Charot and C. Wagner 


Reid B. Porter, Jan R. Frigo, Maya Gokhale

Los Alamos National Lab, USA


    We propose a run-time re-configurable parametric architecture (Fabric) for local neighborhood image processing. The proposed architecture is composed of polymorphous cells where each cell accesses neighborhood data from a local cell memory, and executes a neighborhood function sequentially.

    The architecture is flexible since different neighborhood functions can be implemented by rewriting a cell's software micro-code. High throughput is achieved because many cells execute concurrently. We show that for a satellite image feature extraction application, our architecture, implemented on Stratix II and Virtex 2 Field Programmable Gate Arrays, achieves similar performance, hardware resource utilization, and throughput as a fully pipelined systolic array architecture, yet offers improved flexibility to the developer.