There are three major architectural models used in high-performance signal/image processing: (1) VLSI- signal processing - high- throughput VLSI architectures for low-cost application-specific implementations used in applications such as communication systems, speech, video/HDTV, and radar; (2) parallel signal processing on massively parallel computers - parallel algorithms for complex signal/imaging systems used in computer vision, medical imaging, and the processing of vast amounts of data in deep space exploration; (3) distributed signal processing on high-speed networks - used in applications such as document image processing, multimedia, automatic signal processing in manufacturing, and medical signal/image processing. This research will focus on the development of efficient algorithms and architectures for each architectural model, and in comparative studies of the advantages and disadvantages of these different computing schemes. The goal is to investigate which signal/image processing problems can be carried out optimally under different computing and communication schemes.
