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Proceedings Paper

Parallel robust relaxation algorithm for automatic stereo analysis
Author(s): Kannappan Palaniappan; Jozsef Vass; Xinhua Zhuang
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Paper Abstract

A parallel robust relaxation algorithm is proposed to improve the detection and correction of illegal disparities encountered in the automatic stereo analysis (ASA) algorithm. Outliers and noisy matches from correlation-based ASA matching are improved by relaxation labeling and robust statistical methods at each stage of the multiresolution coarse-to-fine analysis. A parallel version of the relaxation labeling algorithm has been implemented for the MasPar supercomputer. The performance scales quite linearly with the number of processing elements and scales better than linear with increasing work load. The algorithm is highly scalable both as the number of processors are increased for solving a fixed size problem and also as the size of the problem increases.

Paper Details

Date Published: 21 September 1998
PDF: 9 pages
Proc. SPIE 3452, Parallel and Distributed Methods for Image Processing II, (21 September 1998); doi: 10.1117/12.323463
Show Author Affiliations
Kannappan Palaniappan, Univ. of Missouri/Columbia (United States)
Jozsef Vass, Univ. of Missouri/Columbia (United States)
Xinhua Zhuang, Univ. of Missouri/Columbia (United States)

Published in SPIE Proceedings Vol. 3452:
Parallel and Distributed Methods for Image Processing II
Hongchi Shi; Patrick C. Coffield, Editor(s)

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