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Proceedings Paper

GOP, A Paradigm In Hierarchical Image Processing
Author(s): G. H. Granlund; J. Arvidsson; H. Knutsson
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Paper Abstract

The GOP image computer Consists of an algorithmic structure as well as a hardware structure. In the algorithmic structure is employed a new type of information representation, which allows a high degree of data compression. It includes a class of context-sensitive symmetry operations, which have proved very powerful for processing of image information. These features together allow processing in a hierarchical structure, which has proved necessary for effective processing. The hardware structure allows implementation of this class of algorithms, as well as most other image processing operations suggested. The processor has a two-stage architecture, where the first stage has a power corresponding to one billion operations per second, providing a considerable data reduction. The second part allows a flexible combination of partial results at floating point accuracy.

Paper Details

Date Published: 1 November 1982
PDF: 6 pages
Proc. SPIE 0375, Medical Imaging and Image Interpretation, (1 November 1982); doi: 10.1117/12.934671
Show Author Affiliations
G. H. Granlund, Linkoeping University (Sweden)
J. Arvidsson, Linkoeping University (Sweden)
H. Knutsson, Linkoeping University (Sweden)


Published in SPIE Proceedings Vol. 0375:
Medical Imaging and Image Interpretation
Judith M. S. Prewitt, Editor(s)

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