Adaptive noise filtering of sinusoidal signals with unknown nonlinear phase

Rigoberto Juarez-Salazar; Victor H. Diaz-Ramirez

doi:10.1117/12.2273209

24 August 2017 Adaptive noise filtering of sinusoidal signals with unknown nonlinear phase

Rigoberto Juarez-Salazar, Victor H. Diaz-Ramirez

Proceedings Volume 10395, Optics and Photonics for Information Processing XI; 103950X (2017) https://doi.org/10.1117/12.2273209
Event: SPIE Optical Engineering + Applications, 2017, San Diego, California, United States

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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Citation Download Citation

Rigoberto Juarez-Salazar and 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); https://doi.org/10.1117/12.2273209

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