Open AccessEstimation of physically realizable Mueller matrices from experiments using global constrained optimization
Author(s) -
Jawad Ahmad,
Yoshitate Takakura
Publication year - 2008
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.16.014274
Subject(s) - realizability , computer science , simulated annealing , robustness (evolution) , algorithm , quadratic programming , mathematical optimization , sequential quadratic programming , global optimization , mathematics , biochemistry , chemistry , gene
One can explicitly retrieve physically realizable Mueller matrices from quantified intensity data even in the presence of noise. This is done by integrating the physical realizability criterion obtained by Givens and Kostinski, [J. Mod. Opt. 40, 471 (1993)], as an active constraint in a global optimization process. Among different global optimization techniques, two of them have been tested and their robustness analyzed: a deterministic approach based on sequential quadratic programming and a stochastic approach based on constrained simulated annealing algorithms are implemented for this purpose. We illustrate the validity of both methods on experimental data and on the inadmissible Mueller matrix given by Howell, [Appl. Opt. 18, No. 6, 808-812 (1979)]. In comparison, the constrained simulated annealing method produced higher accuracy with similar computing time.