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Proceedings Paper

Data-parallel algorithms for image computing
Author(s): Mark J. Carlotto
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Paper Abstract

Data-parallel algorithms for image computing on the Connection Machine are described. After a brief review of some basic programming concepts in *Lip, a parallel extension of Common Lisp, data-parallel programming paradigms based on a local (diffusion-like) model of computation, the scan model of computation, a general interprocessor communications model, and a region-based model are introduced. Algorithms for connected component labeling, distance transformation, Voronoi diagrams, finding minimum cost paths, local means, shape-from-shading, hidden surface calculations, affine transformation, oblique parallel projection, and spatial operations over regions are presented. An new algorithm for interpolating irregularly spaced data via Voronoi diagrams is also described.

Paper Details

Date Published: 1 November 1990
PDF: 14 pages
Proc. SPIE 1301, Digital Image Processing and Visual Communications Technologies in the Earth and Atmospheric Sciences, (1 November 1990); doi: 10.1117/12.21425
Show Author Affiliations
Mark J. Carlotto, Analytic Sciences Corp. (United States)


Published in SPIE Proceedings Vol. 1301:
Digital Image Processing and Visual Communications Technologies in the Earth and Atmospheric Sciences
Paul Janota, Editor(s)

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