Paper
27 March 1987 An Image Understanding System Based On Macro Data Flow
William W. Wehner
Author Affiliations +
Proceedings Volume 0726, Intelligent Robots and Computer Vision V; (1987) https://doi.org/10.1117/12.937774
Event: Cambridge Symposium_Intelligent Robotics Systems, 1986, Cambridge, MA, United States
Abstract
Current algorithms used in image processing and image understanding applications impose diverse and demanding computational requirements on processor architectures. While general purpose computers can provide the needed types of computation, the performance requirements driven by high-rate imaging sensors force system architects to use highly parallel and/or specialized hardware to attain an efficient system realization. To date, end-to-end systems capable of attaining real-time performance at full sensor data rates have relied on a mixture of processor types generally including specialized hardware for low-level pixel processing and general purpose processors for abstract symbolic data manipulation. Such systems are plagued by several problems: a clean division of algorithms among processor types is difficult and can impose artificial constraints; each processor type requires a different software environment making a unified programming methodology difficult; specialized pixel processing hardware frequently possesses little or no programmability; and programmable processors rely on microcoding to maximize concurrency but make the conversion from course-grained high-order languages difficult. Honeywell's Macro architecture uses data-driven data flow techniques developed for supercomputing to attain high performance parallel computation while simplifying high-order language programming. A compact and efficient processor realization is attained through a system organization which takes advantage of the macro nature of signal and image data and through hardware constructs which make low-level pipelining invisible to the user.
© (1987) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
William W. Wehner "An Image Understanding System Based On Macro Data Flow", Proc. SPIE 0726, Intelligent Robots and Computer Vision V, (27 March 1987); https://doi.org/10.1117/12.937774
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KEYWORDS
Image processing

Image understanding

Transform theory

Computing systems

Signal processing

Computer architecture

Array processing

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