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Optimal signal processing of nonlinearity in swept-source and spectral-domain optical coherence tomography
Author(s) -
Sébastien Vergnole,
Daniel Lévesque,
Kostadinka Bizheva,
Guy Lamouche
Publication year - 2012
Publication title -
applied optics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.668
H-Index - 197
eISSN - 2155-3165
pISSN - 1559-128X
DOI - 10.1364/ao.51.001701
Subject(s) - optics , fourier transform , optical coherence tomography , convolution (computer science) , frequency domain , bessel function , signal processing , computer science , algorithm , physics , mathematics , digital signal processing , mathematical analysis , artificial intelligence , artificial neural network , computer hardware , computer vision
We demonstrate the efficiency of the convolution using an optimized Kaiser-Bessel window to resample nonlinear data in wavenumber for Fourier-domain optical coherence tomography (OCT). We extend our previous experimental demonstration that was performed with a specific swept-source nonlinearity. The method is now applied to swept-source OCT data obtained for various simulated swept-source nonlinearities as well as spectral-domain OCT data obtained from both simulations and experiments. Results show that the new optimized method is the most efficient for handling all the different types of nonlinearities in the wavenumber domain that one can encounter in normal practice. The efficiency of the method is evaluated through comparison with common methods using resampling through interpolation prior to performing a fast-Fourier transform and with the accurate but time-consuming discrete Fourier transform for unequally spaced data, which involves Vandermonde matrices.

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