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Optical spectrum augmentation for machine learning powered spectroscopic ellipsometry

OPTICS EXPRESS 2022年第10期30卷 16909-16920页

作者： Kim, Inho Gwak, Seungho Bae, Yoonsung Jo, Taeyong Samsung Elect Co Ltd Mechatron R&D Ctr 1-1 Samsungjeonja Ro Hwaseong Si 18848 Gyeonggi Do South Korea

As structures of semiconductors become more complex and finer, the importance of an accurate measurement system has emerged. Previous studies have suggested various methodologies to improve the accuracy. However, since multiple measuring instruments are used in mass production, repeatability and reproducibility are as important as the accuracy of the values produced by predictive models. In this study, we adopted a data augmentation approach that minimizes the physical difference between multiple measuring instruments by using the domain knowledge of the spectroscopic ellipsometry (SE) field. By modeling the photodetector misalignment as polynomials and taking into account random noise, we proposed stochastic polynomial wavelength calibration (s-PWC) which can improve the percentage of the gage repeatability and reproducibility (Gage R&R) value. In experiments, the proposed methodology was applied to train the nanostructure prediction model of a three-dimensional vertical NAND Flash memories with industrial data sets. The performance improvements before and after applying the method were evaluated. Gaussian noise augmentation (GNA) and polynomial wavelength calibration (PWC) methodologies devised based on previous studies were also evaluated for relative comparison. As a result of conducting the experiments under conditions similar to the actual production environment, the average value of the percentage of Gage R&R decreased from 10.23% to 6.3% when applying the proposed method, while the GNA and PWC methodologies reduced the values to 10.01% and 7.62%, respectively. There were no significant changes in the values of coefficient of determination (R-2) and root mean square error (RMSE) when applying the three methods based on the data augmentation approach. In other words, applying s-PWC ensures that the predictive model produces consistent values for the same sample when it needs to infer data obtained from multiple measuring instruments, while maintaining R-2 and

关键词： Calibration image processing algorithms Metrological instrumentation Process control Rigorous coupled wave analysis Scanning electron microscopy

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General design algorithm for stray light suppression of a panoramic annular system

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OPTICS EXPRESS 2023年第14期31卷 23491-23506页

作者： Liao, Yiqi Gao, Shaohua Bai, Jian Wang, Kaiwei Zhejiang Univ State Key Lab Modern Opt Instrumentat Hangzhou 310027 Peoples R China Hangzhou Huanjun Technol Co Ltd Hangzhou 310023 Peoples R China

In this work, a universal algorithm for designing a panoramic annular lens (PAL) system free from stray light is proposed. The impact of a given stray light path to the optical system could be estimated without running a full stray light analysis process, which allows designers to eliminate troublesome stray light paths by optimizing lens parameters at an early stage of optical design. A 360 & DEG;x(40 & DEG;-100 & DEG;) PAL system is designed and implemented to verify the proposed method. Simulation shows that the point source transmittance (PST) decreases by 2 orders of magnitude at a specific field-of-view (FoV) range after optimizing the system. Experimental results show perfect consistency with the simulation predictions, which indicate that two types of stray light are totally eliminated in the demonstrated system. This stray light analysis and suppression method provides a promising approach for the research and development of ultra-wide angle high performance optical systems. & COPY;2023 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement

关键词： Bidirectional scattering distribution function Digital image processing image processing algorithms Optical design software Stray light Stray light analysis

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Convolutional dictionary learning for blind deconvolution of optical coherence tomography images

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BIOMEDICAL OPTICS EXPRESS 2022年第4期13卷 1834-1854页

作者： Wang, Junzhe Wohlberg, Brendt Adamson, R. B. A. Dalhousie Univ Sch Biomed Engn Halifax NS B3H 4R2 Canada Los Alamos Natl Lab Theoret Div Los Alamos NM 87545 USA Dalhousie Univ Elect & Comp Engn Dept Halifax NS B3H 4R2 Canada

In this study, we demonstrate a sparsity-regularized, complex, blind deconvolution method for removing sidelobe artefacts and stochastic noise from optical coherence tomography (OCT) images. Our method estimates the complex scattering amplitude of tissue on a line-by-line basis by estimating and deconvolving the complex, one-dimensional axial point spread function (PSF) from measured OCT A-line data. We also present a strategy for employing a sparsity weighting mask to mitigate the loss of speckle brightness within tissue-containing regions caused by the sparse deconvolution. Qualitative and quantitative analyses show that this approach suppresses sidelobe artefacts and background noise better than traditional spectral reshaping techniques, with negligible loss of tissue structure. The technique is particularly useful for emerging OCT applications where OCT images contain strong specular reflections at air-tissue boundaries that create large sidelobe artefacts. (c) 2022 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement

关键词： Blind deconvolution image metrics image processing image processing algorithms image quality Spatial frequency

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Optical Assessment of Tear Glucose by Smart Biosensor Based on Nanoparticle Embedded Contact Lens

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NANO LETTERS 2021年第20期21卷 8933-8940页

作者： Jeon, Hee-Jae Kim, Sooyeon Park, Sijin Jeong, In-Kyung Kang, Jaheon Kim, Young Ro Lee, Dong Yun Chung, Euiheon Gwangju Inst Sci & Technol GIST Dept Biomed Sci & Engn Gwangju 61005 South Korea Purdue Univ Weldon Sch Biomed Engn W Lafayette IN 47907 USA Hanyang Univ Dept Bioengn Coll Engn Seoul 04763 South Korea Hanyang Univ Educ & Res Grp Seoul 04763 South Korea Hanyang Univ Inst Nano Sci & Technol INST Seoul 04763 South Korea Elixir Pharmatech Inc Seoul 04763 South Korea Kyung Hee Univ Kyung Hee Univ Hosp Gangdong Dept Endocrinol & Metab Sch Med Seoul 02447 South Korea Harvard Med Sch Dept Radiol Boston MA 02115 USA Massachusetts Gen Hosp Athinoula A Martinos Ctr Biomed Imaging Charlestown MA 02129 USA GIST AI Grad Sch Gwangju 61005 South Korea GIST Dept Phys & Photon Sci Gwangju 61005 South Korea

Diabetes is a disease condition characterized by a prolonged, high blood glucose level, which may lead to devastating outcomes unless properly managed. Here, we introduce a simple camera-based optical monitoring system (OMS) utilizing the nanoparticle embedded contact lens that produces color changes matching the tear glucose level without any complicated electronic components. Additionally, we propose an image processing algorithm that automatically optimizes the measurement accuracy even in the presence of image blurring, possibly caused by breathing, subtle movements, and eye blinking. As a result, using in vivo mouse models and human tear samples we successfully demonstrated robust correlations across the glucose concentrations measured by three different independent techniques, validating the quantitative efficacy of the proposed OMS. For its methodological simplicity and accessibility, our findings strongly support that the innovation offered by the OMS and processing algorithm would greatly facilitate the glucose monitoring procedure and improve the overall welfare of diabetes patients.

关键词： optical monitoring system (OMS) nanoparticle embedded contact lens (NECLs) image processing algorithms tear glucose

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Method for determination of optical rotatory dispersion curve by using a polarization axis finder

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APPLIED OPTICS 2022年第8期61卷 1965-1971页

作者： Wang, Fujie Lei, Bing Gao, Chao Wen, Xueke Lei, Yu Natl Univ Def Technol Coll Adv Interdisciplinary Studies Changsha 410073 Peoples R China

We report a new, to the best of our knowledge, measurement method of optical rotatory dispersion (ORD) based on a polarization axis finder (PAF) and digital image processing. The collimated quasi-monochromatic light is output by a monochromator and passes through a polarizer and the chiral samples, and a PAF is employed to modulate the light beam spatially to form an "hourglass" intensity pattern, which is utilized to determine the polarization direction of linearly polarized light. After being recorded by a digital camera, the modulated patterns with and without samples are analyzed by our specially designed digital image processing program to calculate the optical rotation (OR) angle of the chiral substance at a certain wavelength, and the ORD curve can be obtained by fitting a series of OR angles with different wavelengths. The ORD curves of two standard quartz plates with opposite chirality and a glucose solution with different concentrations are measured experimentally, and the fitted coefficients and measurement results agree well with their theoretical values, which indicates that the presented method is an effective and accurate way to determine the ORD of chiral substances conveniently. (C) 2022 Optica Publishing Group

关键词： Digital image processing image processing algorithms Light beams Line scan cameras Optical components Stray light

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image restoration for synthetic aperture systems with a non-blind deconvolution algorithm via a deep convolutional neural network

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OPTICS EXPRESS 2020年第7期28卷 9929-9943页

作者： Hui, Mei Wu, Yong Li, Weiqian Liu, Ming Dong, Liquan Kong, Lingqin Zhao, Yuejin Beijing Inst Technol Sch Optoelect Beijing Key Lab Precis Optoelect Measurement Inst Beijing 100081 Peoples R China

Optical synthetic aperture imaging systems, which consist of in-phase circular submirrors, can greatly improve the spatial resolution of a space telescope. Due to the sub-mirrors' dispersion and sparsity, the modulation transfer function is decreased significantly compared to a fully filled aperture system, which causes obvious blurring and loss of contrast in the collected image. image restoration is the key to get the ideal clear image. In this paper, an appropriative non-blind deconvolution algorithm for image restoration of optical synthetic aperture systems is proposed. A synthetic aperture convolutional neural network (CNN) is trained as a denoiser prior to restoring the image. By improving the half-quadratic splitting algorithm, the image restoration process is divided into two subproblems: deconvolution and denoising. The CNN is able to remove noise in the gradient domain and the learned gradients are then used to guide the image deconvolution step. Compared with several conventional algorithms, scores of evaluation indexes of the proposed method are the highest. When the signal to noise ratio is 40 dB, the average peak signal to noise ratio is raised from 23.7 dB of the degraded images to 30.8 dB of the restored images. The structural similarity index of the results is increased from 0.78 to 0.93. Both quantitative and qualitative evaluations demonstrate that the proposed method is effective. (C) 2020 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

关键词： image metrics image processing image processing algorithms Optical transfer functions Stochastic gradient descent Synthetic aperture imaging

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Simulation-driven learning: a deep learning approach for image scanning microscopy via physical imaging models

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OPTICS EXPRESS 2022年第7期30卷 11848-11860页

作者： Zhang, Baoyuan Sun, Xuefeng Yang, Hongxia Guo, Cheng Wu, Biwei Tan, Jiubin Wang, Weibo Harbin Inst Technol Inst Ultraprecis Optoelect Instrument Engn Harbin 150001 Peoples R China Harbin Inst Technol Minist Ind & Informat Technol Key Lab Ultraprecis Intelligent Instrumentat Harbin 150001 Peoples R China

image reconstruction based on deep learning has become an effective tool in fluorescence microscopy. Most deep learning reconstruction methods ignore the mechanism of the imaging process where a large number of datasets are required. In addition, a lot of time is spent solving the aliasing problem from multi-scaled image pairs for data pre-processing. Here we demonstrate an improved generative adversarial network for image scanning microscopy (ISM) that can be trained by simulation data and has good generalization. Based on physical imaging models, this method can generate matching image pairs from simulation images and uses them as datasets for network training, without capturing a large number of real ISM images and avoiding image alignment preprocessing. Simulation and experimental results show that this simulation data-driven method improves the imaging quality of conventional microscopic images and reduces the cost of experiments. This method provides inspiration for optimizing network generalizability of the deep learning network. (C) 2022 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement

关键词： Fluorescence microscopy image processing image processing algorithms image reconstruction image registration Scanning microscopy

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Single-spot two-dimensional displacement measurement based on self-mixing interferometry

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OPTICA 2017年第7期4卷 729-735页

作者： Zhu, Kaiyi Guo, Bo Lu, Yueyue Zhang, Shulian Tan, Yidong Tsinghua Univ State Key Lab Precis Measurement Technol & Instru Dept Precis Instrument Beijing 100084 Peoples R China

The simultaneous and independent measurements of in-plane and out-of-plane displacements are significant issues to be solved in research. Here a novel system to realize single-spot two-dimensional (2D) displacement measurement of a noncooperative target is reported. The performance of the system is tested in the displacement measurement of an aluminum target with a rough surface. 2D random movement and 2D movement with different parameters of Lissajous figures are measured by the system. The ranges of the 2D displacement measurement reach 500 mu m and the accuracies reach the submicron scale. The resolutions of the two dimensions are all better than 5 nm. The measurement system is based on laser heterodyne self-mixing interferometry with frequency multiplexing, which has advantages such as noncontact, nondestruction, nanometer-scale resolution and high sensitivity. The method is promising to be applied in 2D deformation tests of materials, 2D rotor vibration measurement, 2D positioning of particles, thermal expansion coefficient measurement, and other applications. (C) 2017 Optical Society of America

关键词： image processing algorithms Laser beams Laser interferometry Laser sensors Speckle interferometry Three dimensional measurement

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Lensless complex amplitude image retrieval through a visually opaque scattering medium

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APPLIED OPTICS 2017年第16期56卷 4591-4597页

作者： Das, Bhargab Bisht, Nandan S. Vinu, R. V. Singh, Rakesh Kumar Cent Sci Instruments Org CSIR Adv Mat & Sensors Div Sect 30-C Chandigarh 160030 India Kumaun Univ Dept Phys SSJ Campus Almora 263601 Uttarakhand India Indian Inst Space Sci & Technol Dept Phys Appl & Adapt Opt Lab Trivandrum 695547 Kerala India

We propose and experimentally demonstrate lensless complex amplitude image retrieval through a visually opaque scattering medium from spatially fluctuating fields using intensity measurement and a phase-retrieval algorithm. The complex amplitude information of the hidden object is encoded in the form of a real and non-negative amplitude function represented as an interference pattern. A single charge coupled device (CCD) image of the scattered light collected through a visually opaque optical diffuser contains enough information to digitally regenerate the interference pattern. Furthermore, a lensless configuration is implemented which eliminates any possible aberration effects associated with optical components, and this further has promising applications where the use of imaging optics is not feasible. Experimental results for the recovery of complex fields corresponding to optical vortices of two different topological charges are presented. (C) 2017 Optical Society of America

关键词： image processing algorithms Medical imaging Optical components Optical fields Speckle noise Speckle patterns

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Controlled angular and radial scanning for super resolution concentric circular imaging

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OPTICS EXPRESS 2016年第20期24卷 22581-22595页

作者： Du, Xian Anthony, Brian MIT Lab Mfg & Prod 77 Massachusetts Ave Cambridge MA 02139 USA

Poor motion estimation and subsequent registration are detrimental to super-resolution (SR). In this paper, we present a camera sampling method for achieving SR in concentric circular trajectory sampling (CCTS). Using this method, we can precisely control regular radial and angular shifts in CCTS. SR techniques can be subsequently applied ring by ring in radial and angular dimensions. Not only does the proposed camera sampling method eliminate the transient behavior and increases the sampling speed in CCTS, it also preserves the SR accuracy. Our experimental results demonstrate that our approach can accurately discriminate SR pixels from blurry images. (C) 2016 Optical Society of America

关键词： image processing algorithms image quality image reconstruction image registration Imaging techniques Motion estimation

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