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Proceedings Paper

Regularization methods for processing fringe pattern images
Author(s): Jose Luis Marroquin Zaleta; Mariano Rivera; Salvador Botello; Ramon Rodriguez-Vera; Manuel Servin Guirado
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Paper Abstract

A very powerful technique for solving the kind of inverse problems that often arise in the processing of fringe pattern images is based on Bayesian Estimation with prior Markov Random Field models. In this approach, the solution of a processing problem is characterized as the minimizer of a cost function which has two types of terms: terms that specify that the solution should be compatible with the available observations and terms that impose certain constraints on the solution. In this paper we show that by the appropriate choice of these terms, one can use this approach in almost every processing step for accurate interferogram demodulation. Specifically, one can construct: robust smoothing filters that are almost insensitive to edge effects; operators that automatically determine a mask that indicates the shape of the region where valid fringes are available; adaptive quadrature filters for phase recovery from single and multi-phase stepping interferograms and robust phase unwrapping algorithms.

Paper Details

Date Published: 30 June 1998
PDF: 11 pages
Proc. SPIE 3478, Laser Interferometry IX: Techniques and Analysis, (30 June 1998); doi: 10.1117/12.312949
Show Author Affiliations
Jose Luis Marroquin Zaleta, Ctr. de Investigacion en Matematicas, A.C. (Mexico)
Mariano Rivera, Ctr. de Investigacion en Matematicas, A.C. (Mexico)
Salvador Botello, Ctr. de Investigacion en Matematicas, A.C. (Mexico)
Ramon Rodriguez-Vera, Ctr. de Investigaciones en Optica, A.C. (Mexico)
Manuel Servin Guirado, Ctr. de Investigaciones en Optica, A.C. (Mexico)


Published in SPIE Proceedings Vol. 3478:
Laser Interferometry IX: Techniques and Analysis
Malgorzata Kujawinska; Gordon M. Brown; Mitsuo Takeda, Editor(s)

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