2019

• Record 565 of
  
  Title:Automatic Matching Method for Calibration Points Based on an Angular Ordered Sequence
  
  Author(s):Zhong, Lijun(1); Yu, Qifeng(1); Zhou, Jiexin(1); Shang, Yang(1); Zhang, Xiaohu(2); Wang, Tao(3)
  Source: 2019 IEEE 4th International Conference on Image, Vision and Computing, ICIVC 2019  Volume:   Issue:   DOI: 10.1109/ICIVC47709.2019.8980919  Published: July 2019  
  Abstract:The calibration of a camera in wide scene generally requires a large number of non-coplanar control points. This process often needs a large amount of extra auxiliary work to match the object points and the image points, and in some cases, this matching is difficult for users with insufficient experience. A feature representation and optimal priority matching method based on the angular ordered sequences (AOS) of a control point are proposed in this paper with the goal of solving the object-image auto-matching problem for control points. We also provide a strategy for dealing with the difficult situation for automatic calibration when the camera's optical center is nearly collinear with two object points. The simulation results demonstrated that the proposed method was robust with errors for the initial value of the optical center, object points, and image points, and it could quickly achieve object-image matching for automatic calibration. © 2019 IEEE.
  Accession Number: 20201908641553
• Record 566 of
  
  Title:19×1 space incoherent beam combining for 10 kW laser perforation in oil well
  
  Author(s):Zha, Rongwei(1); Lei, Guangzhi(2); Li, Jianlin(1,2); Chen, Haowei(1); Bai, Yang(1)
  Source: Hongwai yu Jiguang Gongcheng/Infrared and Laser Engineering  Volume: 48  Issue: 10  DOI: 10.3788/IRLA201948.1005013  Published: October 25, 2019  
  Abstract:Laser perforation is a forward-looking technology in the oil well completion engineering, which has great application value for improving oil recovery. In order to improve the laser power and laser transmission safety used in oil well laser perforation, 10 kW-laser space incoherent combining was realized by using 19 fiber-transmitted 972 nm semiconductor lasers. By studying the effect of the radii, separation distances of collimated laser beams on the spot overlapping efficiency of combined laser beam, and simulating cross section energy distribution of combined laser beam, the structure design of a 19×1 space incoherent beam combiner was completed. A space incoherent combined laser beam with a single beam shape was achieved within the beam combining length of 300 mm, with a maximum combined power of 10.441 kW, a focal spot diameter of 21 mm, a line width of 2.46 nm and a combined efficiency of 98.2%. Ground laser perforation experiments for sandstone and steel plate were performed using the 10 kW spatial incoherent beam laser with perforation depths of 570 mm and 70 mm, respectively. © 2019, Editorial Board of Journal of Infrared and Laser Engineering. All right reserved.
  Accession Number: 20194807747418
• Record 567 of
  
  Title:Minimized Laplacian residual interpolation for DoFP polarization image demosaicking
  
  Author(s):Jiang, Tuochi(1,2); Wen, Desheng(1); Song, Zongxi(1); Zhang, Weikang(1,2); Li, Zhixin(1,2); Wei, Xin(1,2); Liu, Gang(1,2)
  Source: Applied Optics  Volume: 58  Issue: 27  DOI: 10.1364/AO.58.007367  Published: September 20, 2019  
  Abstract:Division of focal plane (DoFP) polarization imaging sensors have the distinct advantage of acquiring temporally synchronized Stokes vector in one scene. The sensors’ spatially modulated arrangement of a micropolarization array results in loss of spatial resolution and instantaneous field-of-overview errors. Polarization demosaicking (PDM) methods are often utilized to address these drawbacks and achieve the goal of recovering missing polarization information. In this paper, we propose minimized Laplacian polarization residual interpolation for PDM. The Laplacian energy is introduced to improve the interpolation accuracy. We employ interchannel correlation and a guided filter to generate precise tentative estimates and the interpolation performed in the residual domain, where the residuals are the differences between observed values and tentative estimates. Experiments demonstrate that the proposed algorithm provides superior performance in terms of mean average error and peak signal-to-noise ratio. © 2019 Optical Society of America.
  Accession Number: 20193907462941
• Record 568 of
  
  Title:Influence of Layup Sequence on the Surface Accuracy of Carbon Fiber Composite Space Mirrors
  
  Author(s):Yang, Zhiyong(1,2); Liu, Qingnian(2); Zhang, Boming(1); Xu, Liang(3); Tang, Zhanwen(2); Xie, Yongjie(3)
  Source: Applied Composite Materials  Volume: 26  Issue: 1  DOI: 10.1007/s10443-018-9690-4  Published: February 1, 2019  
  Abstract:Layup sequence is directly related to stiffness and deformation resistance of the composite space mirror, and error caused by layup sequence can affect the surface precision of composite mirrors evidently. Variation of layup sequence with the same total thickness of composite space mirror changes surface form of the composite mirror, which is the focus of our study. In our research, the influence of varied quasi-isotropic stacking sequences and random angular deviation on the surface accuracy of composite space mirrors was investigated through finite element analyses (FEA). We established a simulation model for the studied concave mirror with 500 mm diameter, essential factors of layup sequences and random angular deviations on different plies were discussed. Five guiding findings were described in this study. Increasing total plies, optimizing stacking sequence and keeping consistency of ply alignment in ply placement are effective to improve surface accuracy of composite mirror. © 2018, Springer Science+Business Media B.V., part of Springer Nature.
  Accession Number: 20181504998613
• Record 569 of
  
  Title:An Adaptive Stopping Active Contour Model for Image Segmentation
  
  Author(s):Niu, Yuefeng(1,2); Cao, Jianzhong(1); Zhou, Zuofeng(1)
  Source: Journal of Electrical Engineering and Technology  Volume: 14  Issue: 1  DOI: 10.1007/s42835-018-00030-8  Published: January 30, 2019  
  Abstract:Active contour models (ACMs) are widely used in image segmentation applications. However, the selection of maximum iterations which controls the convergence of the ACMs is still a challenging problem. In this paper, an adaptive method for choosing the optimal number of iterations based on the local and global intensity fitting energy is proposed, which increases the automaticity of the active contour model. Moreover, the adoption of the reaction diffusion (RD) method instead of the distance regularization term can improve the accuracy and speed of segmentation effectively. Experimental results on synthetic and real images show that the proposed model outperforms other representative models in terms of accuracy and efficiency. © 2019, The Korean Institute of Electrical Engineers.
  Accession Number: 20192607096793
• Record 570 of
  
  Title:Local difference-based active contour model for medical image segmentation and bias correction
  
  Author(s):Niu, Yuefeng(1,2); Cao, Jianzhong(1)
  Source: IET Image Processing  Volume: 13  Issue: 10  DOI: 10.1049/iet-ipr.2018.5230  Published: August 22, 2019  
  Abstract:This study proposes a local bias field and difference estimation (LBDE) model for medical image segmentation and bias field correction. Firstly, the LBDE model uses a linear combination of a given set of smooth orthogonal basis functions, which is called Chebyshev polynomial, to estimate the bias field. Then, a clustering criterion function is defined by considering the difference between the measured image and approximated image in a small region. By applying this difference in the local region, the LBDE model can obtain accurate segmentation results and estimation of the bias field. Finally, the energy functional is incorporated into a level set formulation with a regularisation term, and it is minimised via the level set evolution process. The LBDE model first appears as a two-phase model and then extends to the multi-phase one. Extensive experiments on medical images demonstrate that the LBDE model achieves more precise segmentation results in terms of Jaccard similarity and dice similarity coefficient than the comparative models. Therefore the proposed model can increase the segmentation accuracy and robustness to noise. © 2019 Institution of Engineering and Technology. All rights reserved.
  Accession Number: 20193707429100
• Record 571 of
  
  Title:Fiber-optic MZI activity monitoring based on RLS algorithm
  
  Author(s):Wang, Jiayu(1); Xu, Wei(2,3); Dong, Bo(2); Yu, Changyuan(4); Han, Shuying(5)
  Source: 2019 18th International Conference on Optical Communications and Networks, ICOCN 2019  Volume:   Issue:   DOI: 10.1109/ICOCN.2019.8933918  Published: August 2019  
  Abstract:A non-invasive activity monitoring using Mach-Zehnder interferometer (MZI) is presented and recursive least square (RLS) algorithm is performed to classify presence and absence activity states with accuracy higher than 98.5% within 1 second. © 2019 IEEE.
  Accession Number: 20200408062970
• Record 572 of
  
  Title:Endmember extraction from hyperspectral imagery based on QR factorisation using givens rotations
  
  Author(s):Gan, Yuquan(1,2); Hu, Bingliang(1); Liu, Weihua(1); Wang, Shuang(1); Zhang, Geng(1); Feng, Xiangpeng(1); Wen, Desheng(1)
  Source: IET Image Processing  Volume: 13  Issue: 2  DOI: 10.1049/iet-ipr.2018.5079  Published: February 7, 2019  
  Abstract:Hyperspectral images are mixtures of spectra of materials in a scene. Accurate analysis of hyperspectral image requires spectral unmixing. The result of spectral unmixing is the material spectral signatures and their corresponding fractions. The materials are called endmembers. Endmember extraction equals to acquire spectral signatures of the materials. In this study, the authors propose a new hyperspectral endmember extraction algorithm for hyperspectral image based on QR factorisation using Givens rotations (EEGR). Evaluation of the algorithm is demonstrated by comparing its performance with two popular endmember extraction methods, which are vertex component analysis (VCA) and maximum volume by householder transformation (MVHT). Both simulated mixtures and real hyperspectral image are applied to the three algorithms, and the quantitative analysis of them is presented. EEGR exhibits better performance than VCA and MVHT. Moreover EEGR algorithm is convenient to implement parallel computing for real-time applications based on the hardware features of Givens rotations. © The Institution of Engineering and Technology 2018.
  Accession Number: 20190906561915
• Record 573 of
  
  Title:The infrared moving target extraction and fast video reconstruction algorithm
  
  Author(s):Qiu, Shi(1); Tang, Ying(2); Du, Yun(1,3,4); Yang, Song(5)
  Source: Infrared Physics and Technology  Volume: 97  Issue:   DOI: 10.1016/j.infrared.2018.11.025  Published: March 2019  
  Abstract:Due to the problems of targets submerged to the background, which could easily produce ghosts, and hard complete extraction of dim targets in the surveillance video, we propose the moving target extraction and fast video reconstruction algorithm in accord with visual principle. The sample selection strategy of VIBE algorithm is improved to alleviate the errors of pixel classification. The infrared imaging features are fused to suppress the artifact. A regional growth mechanism is established to extract and store moving targets and pure background regions, and according to the characteristics of video surveillance, it is the first to establish the mapping mechanism of target, background and video to propose the fast video reconstruction algorithm. The experiment shows that the algorithm can extract the moving target completely, establish the pure background in a variety of complex conditions, and greatly reduce the storage room of the surveillance video. © 2018
  Accession Number: 20185206317414
• Record 574 of
  
  Title:Microwave and Communications Applications of Microcombs
  
  Author(s):Xu, Xingyuan(1); Wu, Jiayang(1); Tan, Mengxi(1); Nguyen, Thach(2); Chu, Sai T.(3); Little, Brent E.(4); Morandotti, Roberto(5); Mitchell, Arnan(1); Moss, David J.(1)
  Source: 2019 Conference on Lasers and Electro-Optics, CLEO 2019 - Proceedings  Volume:   Issue:   DOI: 10.23919/CLEO.2019.8749545  Published: May 2019  
  Abstract:We review our recent work in the use of integrated micro-resonator based optical frequency comb sources as the basis for transversal filtering functions for microwave and radio frequency photonic filtering and advanced functions. We demonstrate a range of novel functions including a Hilbert Transform, first, second and third order RF differentiation, true time delays, an RF channelizer and other functions. © 2019 OSA.
  Accession Number: 20192907216731
• Record 575 of
  
  Title:From Deterministic to Generative: Multimodal Stochastic RNNs for Video Captioning
  
  Author(s):Song, Jingkuan(1); Guo, Yuyu(1); Gao, Lianli(1); Li, Xuelong(2); Hanjalic, Alan(3); Shen, Heng Tao(1)
  Source: IEEE Transactions on Neural Networks and Learning Systems  Volume: 30  Issue: 10  DOI: 10.1109/TNNLS.2018.2851077  Published: October 2019  
  Abstract:Video captioning, in essential, is a complex natural process, which is affected by various uncertainties stemming from video content, subjective judgment, and so on. In this paper, we build on the recent progress in using encoder-decoder framework for video captioning and address what we find to be a critical deficiency of the existing methods that most of the decoders propagate deterministic hidden states. Such complex uncertainty cannot be modeled efficiently by the deterministic models. In this paper, we propose a generative approach, referred to as multimodal stochastic recurrent neural networks (MS-RNNs), which models the uncertainty observed in the data using latent stochastic variables. Therefore, MS-RNN can improve the performance of video captioning and generate multiple sentences to describe a video considering different random factors. Specifically, a multimodal long short-Term memory (LSTM) is first proposed to interact with both visual and textual features to capture a high-level representation. Then, a backward stochastic LSTM is proposed to support uncertainty propagation by introducing latent variables. Experimental results on the challenging data sets, microsoft video description and microsoft research video-To-Text, show that our proposed MS-RNN approach outperforms the state-of-The-Art video captioning benchmarks. © 2012 IEEE.
  Accession Number: 20183405732099
• Record 576 of
  
  Title:Broadband photonic RF channelizer based on micro-combs
  
  Author(s):Xu, Xingyuan(1); Wu, Jiayang(1); Tan, Mengxi(1); Nguyen, Thach G.(2); Chu, Sai T.(3); Little, Brent E.(4); Morandotti, Roberto(5); Mitchell, Arnan(2); Moss, David J.(1)
  Source: Proceedings of SPIE - The International Society for Optical Engineering  Volume: 10917  Issue:   DOI: 10.1117/12.2506942  Published: 2019  
  Abstract:In this paper, we first employ CMOS-compatible integrated optical combs to demonstrate a broadband RF channelizer. By using an on-chip nonlinear micro-ring resonator, a broadband 200GHz-spacing Kerr comb with a large number of comb lines are generated, providing a record large number of wavelength channels (over 60 in the C- and L- band) as well as over 100GHz potential RF operation bandwidth for RF channelizers with greatly reduced size, potential cost, and complexity. Record-high spectral slice resolution of 124.94 MHz is achieved through an on-chip MRR featuring a high Q factor up to 1.549×106. As a result, broadband channelization of RF frequencies ranging from 1.7 GHz to 19 GHz is experimentally demonstrated, verifying our approach's feasibility and effectiveness towards the realization of broadband RF channelizer with large channel number and high resolution, as well as reduced cost and footprint. © 2019 SPIE.
  Accession Number: 20192206974767