scholarly journals Recent advances in speckle decorrelation modeling and processing in digital holographic interferometry

2021 ◽  
Vol 13 (4) ◽  
pp. 73
Author(s):  
Pascal Picart
Keyword(s):  
Deep Learning ◽  
Holographic Interferometry ◽  
High Speed ◽  
Digital Holography ◽  
Speckle Noise ◽  
Noise Removal ◽  
Surface Shape ◽  
Full Field ◽  
Recent Advances ◽  
Phase Data

Digital holography, and especially digital holographic interferometry, is a powerful approach for the characterization of modifications at the surface or in the volume of objects. Nevertheless, the reconstructed phase data from holographic interferometry is corrupted by the speckle noise. In this paper, we discuss on recent advances in speckle decorrelation noise removal. Two main topics are considered. The first one presents recent results in modelling the decorrelation noise in digital Fresnel holography. Especially the anisotropy of the decorrelation noise is established. The second topic presents a new approach for speckle de-noising using deep convolution neural networks. Full Text: PDF ReferencesP. Picart (ed.), New techniques in digital holography (John Wiley & Sons, 2015). CrossRef T.M. Biewer, J.C. Sawyer, C.D. Smith, C.E. Thomas, "Dual laser holography for in situ measurement of plasma facing component erosion (invited)", Rev. Sci. Instr. 89, 10J123 (2018). CrossRef M. Fratz, T. Beckmann, J. Anders, A. Bertz, M. Bayer, T. Gießler, C. Nemeth, D. Carl, "Inline application of digital holography [Invited]", Appl. Opt. 58(34), G120 (2019). CrossRef M.P. Georges, J.-F. Vandenrijt, C. Thizy, Y. Stockman, P. Queeckers, F. Dubois, D. Doyle, "Digital holographic interferometry with CO2 lasers and diffuse illumination applied to large space reflector metrology [Invited]", Appl. Opt. 52(1), A102 (2013). CrossRef E. Meteyer, F. Foucart, M. Secail-Geraud, P. Picart, C. Pezerat, "Full-field force identification with high-speed digital holography", Mech. Syst. Signal Process. 164 (2022). CrossRef L. Lagny, M. Secail-Geraud, J. Le Meur, S. Montresor, K. Heggarty, C. Pezerat, P. Picart, "Visualization of travelling waves propagating in a plate equipped with 2D ABH using wide-field holographic vibrometry", J. Sound Vib. 461 114925 (2019). CrossRef L. Valzania, Y. Zhao, L. Rong, D. Wang, M. Georges, E. Hack, P. Zolliker, "THz coherent lensless imaging", Appl. Opt. 58, G256 (2019). CrossRef V. Bianco, P. Memmolo, M. Leo, S. Montresor, C. Distante, M. Paturzo, P. Picart, B. Javidi, P. Ferraro, "Strategies for reducing speckle noise in digital holography", Light: Sci. Appl. 7(1), 1 (2018). CrossRef V. Bianco, P. Memmolo, M. Paturzo, A. Finizio, B. Javidi, P. Ferraro, "Quasi noise-free digital holography", Light. Sci. Appl. 5(9), e16142 (2016). CrossRef R. Horisaki, R. Takagi, J. Tanida, "Deep-learning-generated holography", Appl. Opt. 57(14), 3859 (2018). CrossRef E. Meteyer, F. Foucart, C. Pezerat, P. Picart, "Modeling of speckle decorrelation in digital Fresnel holographic interferometry", Opt. Expr. 29(22), 36180 (2021). CrossRef M. Piniard, B. Sorrente, G. Hug, P. Picart, "Theoretical analysis of surface-shape-induced decorrelation noise in multi-wavelength digital holography", Opt. Expr. 29(10), 14720 (2021). CrossRef P. Picart, S. Montresor, O. Sakharuk, L. Muravsky, "Refocus criterion based on maximization of the coherence factor in digital three-wavelength holographic interferometry", Opt. Lett. 42(2), 275 (2017). CrossRef P. Picart, J. Leval, "General theoretical formulation of image formation in digital Fresnel holography", J. Opt. Soc. Am. A 25, 1744 (2008). CrossRef S. Montresor, P. Picart, "Quantitative appraisal for noise reduction in digital holographic phase imaging", Opt. Expr. 24(13), 14322 (2016). CrossRef S. Montresor, M. Tahon, A. Laurent, P. Picart, "Computational de-noising based on deep learning for phase data in digital holographic interferometry", APL Photonics 5(3), 030802 (2020). CrossRef M. Tahon, S. Montresor, P. Picart, "Towards Reduced CNNs for De-Noising Phase Images Corrupted with Speckle Noise", Photonics 8(7), 255 (2021). CrossRef E. Meteyer, S. Montresor, F. Foucart, J. Le Meur, K. Heggarty, C. Pezerat, P. Picart, "Lock-in vibration retrieval based on high-speed full-field coherent imaging", Sci. Rep. 11(1), 1 (2021). CrossRef

scholarly journals Computational de-noising based on deep learning for phase data in digital holographic interferometry

APL Photonics ◽  
2020 ◽  
Vol 5 (3) ◽  
pp. 030802 ◽  
Author(s):  
Silvio Montresor ◽  
Marie Tahon ◽  
Antoine Laurent ◽  
Pascal Picart
Keyword(s):  
Deep Learning ◽  
Holographic Interferometry ◽  
Phase Data

scholarly journals A Deep Learning Framework for Damage Assessment of Composite Sandwich Structures

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Viviana Meruane ◽  
Diego Aichele ◽  
Rafael Ruiz ◽  
Enrique López Droguett
Keyword(s):  
Deep Learning ◽  
Damage Assessment ◽  
Composite Structures ◽  
High Speed ◽  
Vibration Mode ◽  
Sandwich Structures ◽  
Mode Shapes ◽  
Full Field ◽  
Composite Sandwich ◽  
Composite Sandwich Structures

The vibrational behavior of composite structures has been demonstrated as a useful feature for identifying debonding damage. The precision of the damage localization can be greatly improved by the addition of more measuring points. Therefore, full-field vibration measurements, such as those obtained using high-speed digital image correlation (DIC) techniques, are particularly useful. In this study, deep learning techniques, which have demonstrated excellent performance in image classification and segmentation, are incorporated into a novel approach for assessing damage in composite structures. This article presents a damage-assessment algorithm for composite sandwich structures that uses full-field vibration mode shapes and deep learning. First, the vibration mode shapes are identified using high-speed 3D DIC measurements. Then, Gaussian process regression is implemented to estimate the mode shape curvatures, and a baseline-free gapped smoothing method is applied to compute the damage images. The damage indices, which are represented as grayscale images, are processed using a convolutional-neural-network-based algorithm to automatically identify damaged regions. The proposed methodology is validated using numerical and experimental data from a composite sandwich panel with different damage configurations.

Noise Filter for Surface Shape Measurement in Digital Holography

2019 ◽  
Vol 888 ◽  
pp. 47-51 ◽  
Author(s):  
Yoshitaka Takahashi ◽  
Masakazu Shingu ◽  
Masatoshi Saito ◽  
Toru Nakajima ◽  
Ryutaro Sekiguchi ◽  
...  
Keyword(s):  
Digital Holography ◽  
Moving Average ◽  
Speckle Noise ◽  
Surface Shape ◽  
Shape Measurement ◽  
Shape Information ◽  
Difference Image ◽  
Noise Filter ◽  
Contact Shape ◽  
Average Filter

Phase difference image using phase-shifting digital holography is one of the prospective methods for non-contact shape measurement. For the application, filtering of the obtained image is needed to reduce the speckle noise. Conventional filter, e.g. moving average filter, causes loss of the shape information especially around the region with high steepness. To solve this problem novel filter has been developed that kept steepness of the shape in noise reduction. The filtered data were compared with conventionally filtering ones and the former was closer to the data observed by a laser measuring microscope.

Increment of lateral resolution in digital holography by speckle noise removal

Optik ◽  
2010 ◽  
Vol 121 (22) ◽  
pp. 2049-2052 ◽  
Author(s):  
Freddy Alberto Monroy ◽  
Jorge Garcia-Sucerquia
Keyword(s):  
Digital Holography ◽  
Speckle Noise ◽  
Noise Removal ◽  
Lateral Resolution

Full-field force identification with high-speed digital holography

2022 ◽  
Vol 164 ◽  
pp. 108215
Author(s):  
Erwan Meteyer ◽  
Felix Foucart ◽  
Mathieu Secail-Geraud ◽  
Pascal Picart ◽  
Charles Pezerat
Keyword(s):  
High Speed ◽  
Digital Holography ◽  
Force Identification ◽  
Full Field ◽  
Field Force

scholarly journals Shape and deformation measurements of rough surfaces by phase-shifting digital holography

2021 ◽  
Vol 13 (4) ◽  
pp. 70
Author(s):  
Ichirou Yamaguchi
Keyword(s):  
Digital Holography ◽  
Noise Suppression ◽  
Rough Surfaces ◽  
Speckle Noise ◽  
Photonic Devices ◽  
Phase Shifting ◽  
Surface Shape ◽  
Shape Measurement ◽  
Optical Surfaces ◽  
Digital Holograms

In digital holography recording as reconstruction of holograms are performed digitally by modern photonic devices to increase of optical non-contacting measurements of various kinds of surfaces including both specular and rough surfaces. In this article we discusses these features of digital holography using phase shifting techniques that has much extended its capabilities. Full Text: PDF ReferencesG. Bruning, D.R. Herriott, J.E. Gallagher, D.P. Rosenfeld, A.D. White, D.J. Brangaccio, "Digital Wavefront Measuring Interferometer for Testing Optical Surfaces and Lenses", Appl. Opt. 13, 2693 (1974). CrossRef I. Yamaguchi, T. Zhang, "Phase-shifting digital holography", Opt. Lett. 22, 1268 (1997). CrossRef F. Zhang, I. Yamaguchi, L.P. Yaroslavsky, "Algorithm for reconstruction of digital holograms with adjustable magnification", Opt. Lett. 29, 1668 (2004). CrossRef I. Yamaguchi, "Holography, speckle, and computers", Optics and Lasers in Engineering 39, 411 (2003). CrossRef I. Yamaguchi, M. Yokota, "Speckle noise suppression in measurement by phase-shifting digital holography", Opt. Eng. 48 085602 (2009). CrossRef I. Yamaguchi, J. Kato, S. Ohta, "Surface Shape Measurement by Phase-Shifting Digital Holography", Opt. Rev. 8, 85 (2001). CrossRef I. Yamaguchi, J. Kato, H. Matsuzaki, "Measurement of surface shape and deformation by phase-shifting image digital holography", Opt. Eng. 42, 1267 (2003). CrossRef F. Zhang, J.D.R. Valera, I. Yamaguchi, M. Yokota, G. Mills, "Vibration Analysis by Phase Shifting Digital Holography", Opt. Rev. 11, 5 (2004). CrossRef

Determination of optical field generated by a microlens using digital holographic method

2009 ◽  
Vol 17 (3) ◽  
Author(s):  
T. Kozacki ◽  
M. Józwik ◽  
R. Jóźwicki
Keyword(s):  
Digital Holography ◽  
Focal Length ◽  
Measurement Data ◽  
Ccd Camera ◽  
Surface Shape ◽  
Holographic Method ◽  
Full Field ◽  
Laboratory Setup ◽  
Precise Shape ◽  
Additional Reference

AbstractIn the paper, application of the digital holographic method for full field characterization of the beam generated by microlenses is considered. For this goal, the laboratory setup was designed based on Mach-Zehnder interferometry with the additional reference channel. The beam generated by a microlens was imaged by an afocal system and intensity distributions or interferograms (holograms) were registered by CCD camera. The digital holography using one image allows us to determine microlens parameters, i.e., focal length, aberrations, and shape. The optimum conditions to determine the surface shape of a microlens using holographic method have been found. We compare obtained results with geometrical and interferometric measurements. We show the advantage of digital holography for a shape microlens determination (improved accuracy), aberrations, and focal length (characterization facility). Through optimum refocusing, the digital holography gives more precise shape. The paper is accompanied with computer simulations and the experimental measurement data for geometrical, interferometric, and holographic methods.

Recent Advances in Ultra-High-Speed Waveguide Photodiodes for Optical Communication Systems

2009 ◽  
Vol E92-C (7) ◽  
pp. 922-928 ◽  
Author(s):  
Kikuo MAKITA ◽  
Kazuhiro SHIBA ◽  
Takeshi NAKATA ◽  
Emiko MIZUKI ◽  
Sawaki WATANABE
Keyword(s):  
Optical Communication ◽  
Communication Systems ◽  
High Speed ◽  
Recent Advances ◽  
Ultra High Speed ◽  
Optical Communication Systems
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