Regularization methods for processing fringe pattern images

Jose Luis Marroquin Zaleta; Mariano Rivera; Salvador Botello; Ramon Rodriguez-Vera; Manuel Servin Guirado

doi:10.1117/12.312949

30 June 1998 Regularization methods for processing fringe pattern images

Jose Luis Marroquin Zaleta, Mariano Rivera, Salvador Botello, Ramon Rodriguez-Vera, Manuel Servin Guirado

Proceedings Volume 3478, Laser Interferometry IX: Techniques and Analysis; (1998) https://doi.org/10.1117/12.312949
Event: SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, 1998, San Diego, CA, United States

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.

Citation Download Citation

Jose Luis Marroquin Zaleta, Mariano Rivera, Salvador Botello, Ramon Rodriguez-Vera, and Manuel Servin Guirado "Regularization methods for processing fringe pattern images", Proc. SPIE 3478, Laser Interferometry IX: Techniques and Analysis, (30 June 1998); https://doi.org/10.1117/12.312949

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