Abstract
The authors present a critical survey of parallel architectures and algorithms for image processing. The emphasis is on single-instruction-stream, multiple-data-stream (SIMD) computers with nonshared memory. A number of parallel architectures are discussed and compared. They fall into three categories: mesh-connected computers, pyramid computers, and hypercube and related computers. A set of seven image processing and computer vision tasks is selected, and algorithms for performing these seven tasks on each of the three categories of computers are given. All of the algorithms are evaluated using asymptotic (big-Oh) analysis. An analysis of parallel algorithms for several-pixel level, intermediate level, and high-level image processing tasks is presented. The effects of architectural decisions on algorithms design are examined in detail.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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