High-speed imaging of sound using parallel phase-shifting interferometry

Ishikawa, Kenji; Yatabe, Kohei; Chitanont, Nachanant; Ikeda, Yusuke; Oikawa, Yasuhiro; Onuma, Takashi; Niwa, Hayato; Yoshii, Minoru

doi:10.1364/oe.24.012922

Cited by 91 publications

(29 citation statements)

References 40 publications

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“…x y L L   pixels. Firstly we estimate the background of the fringes as,    C (7) We now find the N eigenvalues  n and eigenvectors v n of matrix C as, (8) Assuming that the largest eigenvalues are 0 1 ( , )…”

Section: Pca-npsa Phase Demodulation Formulamentioning

confidence: 99%

Fourier spectra for nonuniform phase-shifting algorithms based on principal component analysis

Servı́n¹,

Padilla²,

Garnica³

et al. 2019

Opt. Express

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We develop an error-free, nonuniform phase-stepping algorithm (nPSA) based on principal component analysis (PCA). PCA-based algorithms typically give phasedemodulation errors when applied to nonuniform phase-shifted interferograms. We present a straightforward way to correct those PCA phase-demodulation errors. We give mathematical formulas to fully analyze PCA-based nPSA (PCA-nPSA). These formulas give a) the PCA-nPSA frequency transfer function (FTF), b) its corrected Lissajous figure, c) the corrected PCA-nPSA formula, d) its harmonic robustness (R H ), and e) its signal-to-noise-ratio (SNR). We show that the PCA-nPSA can be seen as a linear quadrature filter, and as consequence, one can find its FTF. Using the FTF, we show why plain PCA often fails to demodulate nonuniform phase-shifted fringes. Previous works on PCA-nPSA (without FTF), give specific numerical/experimental fringe data to "visually demonstrate" that their new nPSA works better than competitors. This often leads to biased/favorable fringe pattern selections which "visually demonstrate" the superior performance of their new nPSA. This biasing is herein totally avoided because we provide figures-of-merit formulas based on linear systems and stochastic process theories. However, and for illustrative purposes only, we provide specific fringe data phase-demodulation, including comprehensive analysis and comparisons.2019-04-01 Centro de Investigaciones en Optica A. C.

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Section: Pca-npsa Phase Demodulation Formulamentioning

confidence: 99%

Fourier spectra for nonuniform phase-shifting algorithms based on principal component analysis

Servı́n¹,

Padilla²,

Garnica³

et al. 2019

Opt. Express

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“…Sound field visualization technology is utilized for noise source detection, acoustical design, and other applications. In previous studies, sound field visualization has been realized with various measurement methods, such as acoustical holography [1,2], beam-forming [3,4], and optical methods [5][6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Visualization system for sound field using see-through head-mounted display

Inoue

Ikeda

Yatabe

et al. 2019

Acoust. Sci. & Tech.

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For the visualization of a sound field, a widely used method is the superimposition of the sound information onto a camera view. Although it effectively enables the understanding the relationship between space and sound, a planar display cannot resolve depth information in a straightforward manner. In contrast, a see-through head-mounted display (STHMD) is capable of representing three-dimensional (3D) vision and natural augmented reality (AR) or mixed reality (MR). In this paper, we propose a system for the measurement and visualization of a sound field with an STHMD. We created two visualization systems using different types of STHMDs and technologies for realizing AR/MR and a measurement system for a 3D sound intensity map, which can be used together with the visualization system. Through three visualization experiments, we empirically found that the stereoscopic viewing and the convenient viewpoint movement associated with the STHMD enables understanding of the sound field in a short time.

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“…The weak changes of the refractive index in the transparent medium where the light propagates produce a modulation of the optical path along the trajectory of the laser beam. The phase shift induced by this modulation, that can be measured using interferometers, [5][6][7][8] represents the integration of pressure changes over the laser trajectory.…”

Section: Introductionmentioning

confidence: 99%

Visualization of an acoustic stationary wave by optical feedback interferometry

et al. 2018

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This paper presents a novel experimental technique for 2D imaging of dynamic acoustic pressure changes that is applied to visualize a stationary acoustic wave. This technique uses the optical feedback interferometry sensing scheme with a near infrared laser diode and a two-axis scanning system. The stationary acoustic wave is generated by using a 40 kHz piezoelectric transducer pointing towards a concave acoustic reflector. The acoustic pressure dynamic changes are measured thanks to its impact on the propagating medium refractive index which variation is integrated along the laser optical path from the laser diode to a distant mirror and back. The imaging system records a 100x50 pixels image of the acoustic pressure in 66 minutes.

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High-speed imaging of sound using parallel phase-shifting interferometry

Cited by 91 publications

References 40 publications

Fourier spectra for nonuniform phase-shifting algorithms based on principal component analysis

Fourier spectra for nonuniform phase-shifting algorithms based on principal component analysis

Visualization system for sound field using see-through head-mounted display

Visualization of an acoustic stationary wave by optical feedback interferometry

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