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.
© (1990) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mark J. Carlotto "Data-parallel algorithms for image computing", Proc. SPIE 1301, Digital Image Processing and Visual Communications Technologies in the Earth and Atmospheric Sciences, (1 November 1990); https://doi.org/10.1117/12.21425
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KEYWORDS
Image processing

Diffusion

Digital image processing

Data modeling

Visual communications

Computer programming

Curium

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