24 August 2017 Adaptive noise filtering of sinusoidal signals with unknown nonlinear phase
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Abstract
A self-tuning filter for noise reduction in sinusoidal signals is proposed. Unlike the conventional sine fitting methods, no a priori knowledge of the encoded phase distribution is assumed. For this, an analytical model with three parameters (the average, the amplitude of the sinusoid, and the standard deviation of the noise) is used. The estimated standard deviation is used for adaptively tuning the noise filter. Obtained results show the feasibility of the proposal for fringe pattern normalization.
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Rigoberto Juarez-Salazar, Rigoberto Juarez-Salazar, Victor H. Diaz-Ramirez, Victor H. Diaz-Ramirez, } "Adaptive noise filtering of sinusoidal signals with unknown nonlinear phase", Proc. SPIE 10395, Optics and Photonics for Information Processing XI, 103950X (24 August 2017); doi: 10.1117/12.2273209; https://doi.org/10.1117/12.2273209
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