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Single-step method for fiber-optic probe-based full-range spectral domain optical coherence tomography

APPLIED OPTICS 2013年第21期52卷 5143-5151页

作者： Min, Eun Jung Shin, Jun Geun Lee, Jae Hwi Yasuno, Yoshiaki Lee, Byeong Ha Gwangju Inst Sci & Technol Sch Informat & Commun Kwangju 500712 South Korea Univ Tsukuba Inst Appl Phys Tsukuba Ibaraki 3058573 Japan

We propose a single-step method appropriated for a fiber-optic probe-based full-range spectral domain optical coherence tomography (OCT). The fiber-optic probe was scanned over a sample with a magnetically driven actuator. In the reference arm, a phase shift of pi/2 was applied during two neighbor axial scanning, from which the complex spectral interferogram was directly reconstructed. Since the complex-conjugate-free OCT image is obtained by doing just one Fourier transform on the complex interferogram, obtaining the full-range image is simple in algorithm and effective in computation time. Some full-range images of biological samples created with the proposed method are presented and the processing time is analyzed. (C) 2013 Optical Society of America

关键词： Fourier transforms image processing image processing algorithms Phase modulation Phase shift Spectral domain optical coherence tomography

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Opti-MSFA: a toolbox for generalized design and optimization of multispectral filter arrays

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OPTICS EXPRESS 2022年第5期30卷 7591-7611页

作者： Sawyer, Travis W. Taylor-Williams, Michaela Tao, Ran Xia, Ruqiao Williams, Calum Bohndiek, Sarah E. Univ Arizona Wyant Coll Opt Sci 1630 E Univ Blvd Tucson AZ 85721 USA Univ Arizona Univ Arizona Hlth Sci 1 670 E Drachman St Tucson AZ 85721 USA Univ Cambridge Dept Phys Cavendish Lab JJ Thomson Ave Cambridge CB3 0HE England Univ Cambridge Canc Res UK Cambridge Inst Robinson Way Cambridge CB2 0RE England Univ Cambridge Elect Engn Div Dept Engn JJ Thomson Ave Cambridge CB3 0FA England

Multispectral imaging captures spatial information across a set of discrete spectral channels and is widely utilized across diverse applications such as remote sensing, industrial inspection, and biomedical imaging. Multispectral filter arrays (MSFAs) are filter mosaics integrated atop image sensors that facilitate cost-effective, compact, snapshot multispectral imaging. MSFAs are pre-configured based on application-where filter channels are selected corresponding to targeted absorption spectra-making the design of optimal MSFAs vital for a given application. Despite the availability of many design and optimization approaches for spectral channel selection and spatial arrangement, major limitations remain. There are few robust approaches for joint spectral-spatial optimization, techniques are typically only applicable to limited datasets and most critically, are not available for general use and improvement by the wider community. Here, we reconcile current MSFA design techniques and present Opti-MSFA: a Python-based open-access toolbox for the centralized design and optimization of MSFAs. Opti-MSFA incorporates established spectral-spatial optimization algorithms, such as gradient descent and simulated annealing, multispectral-RGB image reconstruction, and is applicable to user-defined input of spatial-spectral datasets or imagery. We demonstrate the utility of the toolbox by comparing against other published MSFAs using the standard hyperspectral datasets Samson and Jasper Ridge, and further show application on experimentally acquired fluorescence imaging data. In conjunction with end-user input and collaboration, we foresee the continued development of Opti-MSFA for the benefit of the wider research community. Published by Optica Publishing Group under the terms of the Creative Commons Attribution 4.0 License.

关键词： Absorption spectroscopy image processing algorithms Industrial inspection Medical imaging Multispectral imaging Spectral imaging

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Spatially adaptive image denoising using inter-scale dependence in directionlet domain

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IET image processing 2015年第2期9卷 142-152页

作者： Sethunadh, R. Thomas, Tessamma Indian Space Res Org ISRO Vikram Sarabhai Space Ctr Trivandrum Kerala India Cochin Univ Sci & Technol CUSAT Image & Video Proc Lab Cochin Kerala India

The performance of image processing algorithms can be significantly improved by the application of multi-resolution image representation with directional features. Directionlet transform (DT) is one such representation which has gained popularity over the past few years as an anisotropic, perfect reconstruction and critically sampled basis function with directional vanishing moments along any two directions. In this study, the authors propose a spatially adaptive image denoising scheme for Gaussian noise based on DT by considering the dependences of the directionlet coefficients across different scales. The image is first decomposed using DT and the coefficients so obtained are modelled using a bivariate heavy tailed pdf' with a local variance parameter to account for inter- and intra-scale dependencies of the coefficients. The DT is made adaptive to the local dominant directions in the image by identifying the dominant directions in the spatially segmented image through the computation of a parameter called directional variance'. Bayesian maximum a posteriori' estimator is then used to compute the noise free coefficients from the bivariate models of the signal and noise. The denoised image is obtained from the transform coefficients, which were modified using the bivariate shrinkage function, using directional information and inverse DT. Experimental results show that the bivariate shrinkage in directionlet domain achieves better performance than that in wavelet domain, in terms of numerical and perceptual quality.

关键词： image denoising image resolution image representation Gaussian noise image segmentation transforms spatially adaptive image denoising interscale dependence directionlet domain image processing algorithms multiresolution image representation directional features DT sampled basis function directional vanishing moments Gaussian noise directionlet coefficients image segmentation directional variance noise free coefficients bivariate models transform coefficients bivariate shrinkage function

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Weld feature extraction method based on inter-frame constraint and dynamic template

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JOURNAL OF THE OPTICAL SOCIETY OF AMERICA A-OPTICS image SCIENCE AND VISION 2022年第5期39卷 771-781页

作者： Mei, Zhen Qi, Lizhe Xu, Min Sun, Yunquan Fudan Univ Acad Engn & Technol Shanghai 200433 Peoples R China

Welding as an industrial tailor is key to intelligent manufacturing technology. With the development of robots and digital manufacturing technology, autonomous programming intelligent welding robots have emerged. The seam tracking system based on active vision is widely used because of its high precision and obvious characteristics. However, the complexity of the welding environment, the interference of arc splash, and the reflection and local deformation of the workpiece will affect the extraction of weld characteristics. Based on the correlation and differ-ence of adjacent frames in the continuous welding process, this paper combines the point and line characteristics of laser lines and proposes a weld feature extraction method based on an inter-frame constraint and dynamic tem-plate. The experimental results show that the distance error of the proposed method is within three pixels, and the average processing time of each frame is 9.6 ms. This method can realize weld feature extraction in the case of object reflection, arc splash, and local deformation, and has certain robustness. ?? 2022 Optica Publishing Group

关键词： Feature extraction image fusion image processing image processing algorithms image quality Nonlinear spatial filtering

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Optimization of stereoscopic imager performance by computer simulation of geometrical calibration using optical design software

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OPTICS EXPRESS 2019年第13期27卷 17819-17839页

作者： Gorevoy, Alexey, V Machikhin, Alexander S. Batshev, Vladislav, I Kolyuchkin, Vasiliy Ya Russian Acad Sci Sci & Technol Ctr Unique Instrumentat Lab Acoustoopt Spect 15 Butlerova Str Moscow 117342 Russia Natl Res Univ Moscow Power Engn Univ Inst Automat & Comp Engn Dept Elect Engn & Introscopy 14 Krasnokazarmermaya Str Moscow 111250 Russia Bauman Moscow State Tech Univ Dept Radioelect & Laser Technol 5 2 Ya Baumanskaya Str Moscow 105005 Russia

Stereoscopic imagers are widely used in machine vision for three-dimensional (3D) visualization as well as in non-destructive testing for quantitative characterization of cracks, delamination and other defects. Measurement capability in these systems is provided by a proper combination of the optical parameters and data processing techniques. Conventional approach to their design consists of two sequential stages: optical system design and optimization of calibration and image processing algorithms. Such two-stage procedure often complicates both the hardware and the software, and results in a time-ineffective design procedure and cost-ineffective solution. We demonstrate a more effective approach and propose to estimate errors of 3D measurements at the early optical design stage. We show that computer simulation using optical design software allows not only optimizing optical parameters of the imager but also choosing the most effective mathematical model of the system and the equipment necessary for calibration. We tested the proposed approach on the design of miniature prism-based stereoscopic system and analyzed the impact of various factors (aberrations, tolerances, etc.) as on the image quality, so on the quality of calibration and 3D measurements accuracy. The proposed joint design approach may be highly effective for various measurement systems and applications when both optical parameters and image processing algorithms are not defined in advance and are necessary to be optimized. (C) 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

关键词： Camera calibration Digital image processing image processing algorithms image quality Optical design software Optical systems

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High-precision autocollimation method based on a multiscale convolution neural network for angle measurement

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OPTICS EXPRESS 2022年第16期30卷 29821-29832页

作者： Shi, Jian Li, Yuechao Tao, Zixi Zhang, Daixi Xing, Heyang Tan, Jiubin Harbin Inst Technol Ctr Ultraprecis Optoelect Instrument Engn Harbin 150080 Peoples R China Harbin Inst Technol Minist Ind & Informat Technol Key Lab Ultraprecis Intelligent Instrumentat Harbin 150080 Peoples R China

A high-precision autocollimation method based on multiscale convolution neural network (MSCNN) for angle measurement is proposed. MSCNN is integrated with the traditional measurement model. Using the multiscale representation learning ability of MSCNN, the relationship between spot shape (large-scale feature), gray distribution (small-scale feature), and the influence of aberration and assembly error in the collimating optical path is extracted. The constructed accurate nonlinear measurement model directly improves the uncertainty of angle measurement. Experiments demonstrate that the extended uncertainty reaches 0.29 arcsec (k = 2), approximately 7 times higher than that with the traditional measurement principle, and solves the nonlinear error caused by aberration and assembly error in the autocollimation system. Additionally, this method has a good universality and can be applied to other autocollimation systems. (C) 2022 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement

关键词： Autocollimation image processing algorithms Neural networks Precision metrology Surface measurements Three dimensional measurement

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SNR enhancement with a non-local means image-denoising method for a Φ-OTDR system

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APPLIED OPTICS 2023年第9期62卷 2283-2291页

作者： Li, Junchan Wang, Yu Xiao, Lin Liu, Xin Jin, Baoquan Taiyuan Univ Technol Coll Phys & Optoelect Key Lab Adv Transducers & Intelligent Control Sys Minist Educ & Shanxi Prov Taiyuan 030024 Peoples R China Taiyuan Univ Technol Coll Informat & Comp Taiyuan 030024 Peoples R China State Key Lab Coal & CBM Comin Jincheng 048000 Peoples R China

Orthogonal pulse pairs generated by the polarization beam splitter (PBS) and the polarization maintaining-optical switch (PM-PSW) can effectively suppress the polarization fading in phase-sensitive optical time-domain reflectometry (Phi-OTDR) systems, but the PM-PSW also brings a lot of noise when switching the optical path periodically. Therefore, a non-local means (NLM) image-processing method is proposed to enhance the signal-to-noise ratio (SNR) of a Phi-OTDR system. Compared with the existing traditional noise reduction methods based on the one-dimensional signal, the method makes full use of redundant texture and self-similarity of multidimensional data. The NLM algorithm can obtain the estimated denoising result value of current pixels by the weighted average of pixels with similar neighborhood structures in the Rayleigh temporal-spatial image. To validate the effectiveness of the proposed approach, we have carried out experiments on the actual signals obtained from the Phi-OTDR system. In the experiment, a sinusoidal waveform of 100 Hz is applied at 20.04 km of the optical fiber as a simulated vibration signal. The switching frequency of PM-PSW is set to 30 Hz. The experimental result shows that the SNR of vibration positioning curve is 17.72 dB before denoising. After using the NLM method based on image-processing technology, the SNR reaches 23.39 dB. Experimental results demonstrate that this method is feasible and effective in improving SNR. This will help to realize accurate vibration location and recovery in practical applications. (c) 2023 Optica Publishing Group

关键词： image processing image processing algorithms Optical time domain reflectometry Polarization splitters Time division multiplexing Wavelength division multiplexers

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Measurement of wide frequency range structural microvibrations with a pocket digital camera and sub-pixel techniques

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APPLIED OPTICS 2012年第14期51卷 2664-2671页

作者： Mas, David Espinosa, Julian Roig, Ana B. Ferrer, Belen Perez, Jorge Illueca, Carlos Univ Alicante Inst Fis Aplicada Ciencias & Tecnol E-03080 Alicante Spain Univ Alicante Dep Ing Construcc E-03080 Alicante Spain

Analysis of vibrations and displacements is a hot topic in structural engineering. Although there is a wide variety of methods for vibration analysis, direct measurement of displacements in the mid and high frequency range is not well solved and accurate devices tend to be very expensive. Low-cost systems can be achieved by applying adequate image processing algorithms. In this paper, we propose the use of a commercial pocket digital camera, which is able to register more than 420 frames per second (fps) at low resolution, for accurate measuring of small vibrations and displacements. The method is based on tracking elliptical targets with sub-pixel accuracy. Our proposal is demonstrated at a 10 m distance with a spatial resolution of 0.15 mm. A practical application over a simple structure is given, and the main parameters of an attenuated movement of a steel column after an impulsive impact are determined with a spatial accuracy of 4 mu m. (C) 2012 Optical Society of America

关键词： Analytical techniques Frequency measurement High speed photography image processing image processing algorithms image quality

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Real-time noise reduction based on ground truth free deep learning for optical coherence tomography

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BIOMEDICAL OPTICS EXPRESS 2021年第4期12卷 2027-2040页

作者： Huang, Yong Zhang, Nan Hao, Qun Beijing Inst Technol Sch Opt & Photon 5 South Zhongguancun St Beijing 100081 Peoples R China

Optical coherence tomography (OCT) is a high-resolution non-invasive 3D imaging modality, which has been widely used for biomedical research and clinical studies. The presence of noise on OCT images is inevitable which will cause problems for post-image processing and diagnosis. The frame-averaging technique that acquires multiple OCT images at the same or adjacent locations can enhance the image quality significantly. Both conventional frame averaging methods and deep learning-based methods using averaged frames as ground truth have been reported. However, conventional averaging methods suffer from the limitation of long image acquisition time, while deep learning-based methods require complicated and tedious ground truth label preparation. In this work, we report a deep learning-based noise reduction method that does not require clean images as ground truth for model training. Three network structures, including Unet, super-resolution residual network (SRResNet), and our modified asymmetric convolution-SRResNet (AC-SRResNet), were trained and evaluated using signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), edge preservation index (EPI) and computation time (CT). The effectiveness of these three trained models on OCT images of different samples and different systems was also investigated and confirmed. The SNR improvement for different sample images for L2-loss-trained Unet, SRResNet, and AC-SRResNet are 20.83 dB, 24.88 dB, and 22.19 dB, respectively. The SNR improvement for public images from different system for L1-loss-trained Unet, SRResNet, and AC-SRResNet are 19.36 dB, 20.11 dB, and 22.15 dB, respectively. AC-SRResNet and SRResNet demonstrate better denoising effect than Unet with longer computation time. AC-SRResNet demonstrates better edge preservation capability than SRResNet while Unet is close to AC-SRResNet. Eventually, we incorporated Unet, SRResNet, and AC-SRResNet into our graphic processing unit accelerated OCT imaging system for online n

关键词： image metrics image processing image processing algorithms image quality Noise reduction Three dimensional imaging

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Measurement and correction of lateral distortion in a Fizeau interferometer based on the self-calibration technique

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OPTICS EXPRESS 2022年第20期30卷 36134-36143页

作者： Qiao, Xiaoyue Bai, Yunbo Ding, Guoqing Wang, Weiwei Liu, Shijie Cai, Ping Chen, Xin Su, Rong Chinese Acad Sci Shanghai Inst Opt & Fine Mech Shanghai 201800 Peoples R China Shanghai Jiao Tong Univ Sch Elect Informat & Elect Engn Shanghai 200240 Peoples R China China Russian Belt & Rd Joint Lab Laser Sci Shanghai 201800 Peoples R China

The lateral distortion of a surface measuring Fizeau interferometer may cause distorted image features in the lateral direction, as well as the surface form error in the axial direction (which is a source of the retrace error). Traditional method for lateral distortion measurement requires a high-accuracy calibration plate featuring a grid pattern. Such a calibration plate is not always available, especially when the required accuracy of the grid pattern comes to the order of sub-micrometer or even nanometer level. To remove the dependence on the plate accuracy, we propose a self-calibration method for the measurement and correction of lateral distortion in Fizeau interferometer. The self-calibration technique may separate the lateral distortion and the geometric error of the calibration plate. This method is verified using a 108-mm-aper ture Fizeau interferometer. The experiments show that the form measurement error of a surface tilted at approximately 5 degrees and 16 degrees can be reduced from 92 nm to 43 nm and from 251 nm to 144 nm (peak-to-valley value), respectively, after the distortion correction.

关键词： Electron beam lithography Fizeau interferometry image processing algorithms Interferometric imaging Optical aberrations Optical components

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