2016
DOI: 10.1364/oe.24.004221
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Single shot fringe pattern phase demodulation using Hilbert-Huang transform aided by the principal component analysis

Abstract: Hybrid single shot algorithm for accurate phase demodulation of complex fringe patterns is proposed. It employs empirical mode decomposition based adaptive fringe pattern enhancement (i.e., denoising, background removal and amplitude normalization) and subsequent boosted phase demodulation using 2D Hilbert spiral transform aided by the Principal Component Analysis method for novel, correct and accurate local fringe direction map calculation. Robustness to fringe pattern significant noise, uneven background and… Show more

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Cited by 64 publications
(24 citation statements)
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“…Huang et al [157] developed a new algorithm for analyzing nonlinear and non-stationary data, designated as the Hilbert-Huang transform (HHT). Trusiak et al [158,159] employed HHT to achieve efficient adaptive filtering and accurate phase demodulation by using local fringe direction estimation. As shown in Fig.…”
Section: Noise Resistancementioning
confidence: 99%
“…Huang et al [157] developed a new algorithm for analyzing nonlinear and non-stationary data, designated as the Hilbert-Huang transform (HHT). Trusiak et al [158,159] employed HHT to achieve efficient adaptive filtering and accurate phase demodulation by using local fringe direction estimation. As shown in Fig.…”
Section: Noise Resistancementioning
confidence: 99%
“…where β is the local fringe orientation map, [43][44][45] SPF denotes spiral phase function, F and F −1 denote forward and inverse FT, respectively. The analytic π-hologram grants easy access to the phase map of interest E Q -T A R G E T ; t e m p : i n t r a l i n k -; e 0 0 7 ; 3 2 6 ; 4 2 2…”
Section: Algorithm Implementationmentioning
confidence: 99%
“…The modulation frequency, f , and modualtion function phase, θ, are user controlled parameters. Via the Convolution Theorem, the coherence function of the complete SCI spectrum, g complete , is given by (5), where G nom is the Fourier transform of g nom and M (ν; f, θ) is the Fourier transform of the modulation function, m(ν; f, θ). The final coherence function is normalized to achieve nominal fringe contrast of unity at OP D = 0.…”
Section: Theorymentioning
confidence: 99%