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Proceedings Paper

Noise and object elimination from automatic correlation data by a finite element algorithm
Author(s): Irineu da Silva
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Paper Abstract

The article presents the principal aspects of noise and object elimination from automatic correlation data by applying an algorithm based on the finite element theory. The algorithm developed is based on the establishment of a 3-D surface of finite elements fitted to the coordinates from the automatic correlation data by means of a least square adjustment. Three different approximations are discussed for noise and object elimination: a classical elimination by thresholding the residual errors; elimination by applying the Baarda error detection theory and a deterministic elimination using vectorized contours from an image processing.

Paper Details

Date Published: 1 August 1990
PDF: 8 pages
Proc. SPIE 1395, Close-Range Photogrammetry Meets Machine Vision, 13951W (1 August 1990); doi: 10.1117/12.2294311
Show Author Affiliations
Irineu da Silva, Univ. of São Paulo (Brazil)
Swiss Federal Institute of Technology (Switzerland)


Published in SPIE Proceedings Vol. 1395:
Close-Range Photogrammetry Meets Machine Vision
Armin Gruen; Emmanuel P. Baltsavias, Editor(s)

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