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

IF 0.5 Q4 OPTICS
P. Picart
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引用次数: 0

Abstract

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
数字全息干涉测量中散斑去相关建模与处理研究进展
数字全息,特别是数字全息干涉测量,是表征物体表面或体积变化的有力方法。然而,全息干涉法重建的相位数据受到散斑噪声的破坏。本文讨论了散斑去相关噪声去除的最新进展。主要考虑两个主题。第一部分介绍了数字菲涅耳全息中去相关噪声建模的最新成果。特别是建立了去相关噪声的各向异性。第二个主题提出了一种利用深度卷积神经网络进行散斑去噪的新方法。全文:PDFPicart(编),数字全息术中的新技术(John Wiley & Sons, 2015)。* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *通报89,10J123(2018)。CrossRef M. Fratz, T. Beckmann, J. Anders, A. Bertz, M. Bayer, T. Gießler, C. Nemeth, D. Carl,“数字全息术的内线应用[特邀]”,苹果。Opt. 58(34), G120(2019)。CrossRef M.P. george, j.f。Vandenrijt, C. Thizy, Y. Stockman, P. Queeckers, F. Dubois, D. Doyle,“基于CO2激光和漫射照明的数字全息干涉测量技术在大空间反射器测量中的应用”,中国机械工程学报。光学学报,52(1),A102(2013)。陈晓明,陈晓明,陈晓明,“高速数字全息技术在全场力识别中的应用”,机械工程学报。系统。信号处理。32(2022)。CrossRef L. Lagny, M. secailal - geraud, J. Le Meur, S. Montresor, K. Heggarty, C. Pezerat, P. Picart,“基于宽视场全息振动仪的二维ABH板行波传播可视化”,声学学报,461(2019)。赵CrossRef l . Valzania y l .荣,d . Wang m·乔治·e·哈克·Zolliker”:太赫兹连贯的无透镜的成像”。光学器件58,G256(2019)。[CrossRef . V. Bianco, P. Memmolo, M. Leo, S. Montresor, C. didite, M. Paturzo, P. Picart, B. Javidi, P. Ferraro,“数字全息图像中散斑噪声的降低策略”,光学学报。应用学报,7(1),1(2018)。CrossRef V. Bianco, P. Memmolo, M. Paturzo, A. Finizio, B. Javidi, P. Ferraro,“准无噪声数字全息”,光学。科学。应用科学5(9),e16142(2016)。交叉参考R. Horisaki, R. Takagi, J. Tanida,“深度学习生成全息”,苹果。Opt. 57(14), 3859(2018)。[CrossRef . Meteyer, F. Foucart, C. Pezerat, P. Picart,“数字菲涅耳全息干涉测量的散斑去相关建模”,光学学报,29(22),36180 (2021).]引用本文:王晓明,王晓明,王晓明,“多波长数字全息中表面形状引起的去相关噪声的理论分析”,光学学报,29(10),1472(2021)。张晓明,张晓明,张晓明,“基于相干系数最大化的数字三波长全息干涉法的再聚焦准则”,光学学报,42(2),275(2017)。“数字菲涅耳全息成像的一般理论表述”,中国科学院学报。点。A 25, 1744(2008)。王晓明,王晓明,“数字全息相位成像降噪的定量评价方法”,光学学报,24(3),1422(2016)。CrossRef S. Montresor, M. Tahon, A. Laurent, P. Picart,“基于深度学习的数字全息干涉测量相位数据的计算去噪”,光子学报,5(3),030802(2020)。CrossRef M. Tahon, S. Montresor, P. Picart,“减少cnn对斑点噪声破坏的相位图像去噪”,光子学报8(7),255(2021)。郭志强,陈志强,陈志强,陈志强,“基于高速全场相干成像的锁相振动反演”,计算机科学与技术,2011。众议员11(1),1(2021)。CrossRef
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CiteScore
1.40
自引率
0.00%
发文量
24
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