2019
2019
-
Record 613 of
Title:Histograms of Gaussian normal distribution for 3D feature matching in cluttered scenes
Author(s):Zhou, Wei(1,2,3); Ma, Caiwen(1); Yao, Tong(1,2); Chang, Peng(4); Zhang, Qi(2); Kuijper, Arjan(3)Source: Visual Computer Volume: 35 Issue: 4 DOI: 10.1007/s00371-018-1478-x Published: April 1, 2019Abstract:3D feature descriptors provide essential information to find given models in captured scenes. In practical applications, these scenes often contain clutter. This imposes severe challenges on the 3D object recognition leading to feature mismatches between scenes and models. As such errors are not fully addressed by the existing methods, 3D feature matching still remains a largely unsolved problem. We therefore propose our Histograms of Gaussian Normal Distribution (HGND) for capturing salient feature information on a local reference frame (LRF) that enables us to solve this problem. We define a LRF on each local surface patch by using the eigenvectors of the scatter matrix. Different from the traditional local LRF-based methods, our HGND descriptor is based on the combination of geometrical and spatial information without calculating the distribution of every point and its geometrical information in a local domain. This makes it both simple and efficient. We encode the HGND descriptors in a histogram by the geometrical projected distribution of the normal vectors. These vectors are based on the spatial distribution of the points. We use three public benchmarks, the Bologna, the UWA and the Ca’ Foscari Venezia dataset, to evaluate the speed, robustness, and descriptiveness of our approach. Our experiments demonstrate that the HGND is fast and obtains a more reliable matching rate than state-of-the-art approaches in cluttered situations. ? 2018, Springer-Verlag GmbH Germany, part of Springer Nature.Accession Number: 20180704801860 -
Record 614 of
Title:Reconfigurable fractional microwave signal processor based on a microcomb
Author(s):Tan, Mengxi(1); Xu, Xingyuan(1); Wu, Jiayang(1); Nguyen, Thach G.(2); Chu, Sai T.(3); Little, Brent E.(4); Morandotti, Roberto(5,6,7); Mitchell, Arnan(2); Moss, David J.(1)Source: 2019 IEEE International Topical Meeting on Microwave Photonics, MWP 2019 Volume: Issue: DOI: 10.1109/MWP.2019.8892024 Published: October 2019Abstract:We propose and demonstrate reconfigurable fractional microwave signal processing based on an integrated Kerr optical microcomb. We achieve two forms of microwave signal processing functions-A fractional Hilbert transform as well as a fractional differentiator. For the Hilbert transform we demonstrate a phase shift of 45 degrees-half that of a full Hilbert transform, while for the differentiator we achieve square-root differentiation. For both, we achieve high resolution over a broad bandwidth of 17 GHz with a phase deviation of less than 5{\mathrm {o}} within the achieved passband. This performance in both the frequency and time domains demonstrates the versatility and power of micro-combs as a basis for high performance microwave signal processing. ? 2019 IEEE.Accession Number: 20194807734924 -
Record 615 of
Title:Robust contrast-transfer-function phase retrieval via flexible deep learning networks
Author(s):Bai, Chen(1); Zhou, Meiling(1); Min, Junwei(1); Dang, Shipei(1,2); Yu, Xianghua(1); Zhang, Peng(1); Peng, Tong(1,2,3); Yao, Baoli(1)Source: Optics Letters Volume: 44 Issue: 21 DOI: 10.1364/OL.44.005141 Published: November 1, 2019Abstract:By exploiting the total variation (TV) regularization scheme and the contrast transfer function (CTF), a phase map can be retrieved from single-distance coherent diffraction images via the sparsity of the investigated object. However, the CTF-TV phase retrieval algorithm often struggles in the presence of strong noise, since it is based on the traditional compressive sensing optimization problem. Here, convolutional neural networks, a powerful tool from machine learning, are used to regularize the CTF-based phase retrieval problems and improve the recovery performance. This proposed method, the CTF-Deep phase retrieval algorithm, was tested both via simulations and experiments. The results show that it is robust to noise and fast enough for high-resolution applications, such as in optical, x-ray, or terahertz imaging. ? 2019 Optical Society of America.Accession Number: 20194507632656 -
Record 616 of
Title:Multi-wavelength multi-focus Fresnel solar concentrator with square uniform irradiance: Design and analysis
Author(s):Jiang, Yanru(1,2); Xie, Qingkun(1,2); Qu, Enshi(1); Ren, Liyong(1,3); Liang, Jian(1); Wang, Jing(1,2)Source: Applied Optics Volume: 58 Issue: 19 DOI: 10.1364/AO.58.005206 Published: 2019Abstract:In this paper, a two-step optical design method is proposed to build a superior Fresnel-based photovoltaic concentrator for enhancing light conversion efficiency with the multi-junction solar cell. In the first step, we orthogonally segment a traditional Fresnel concentrator and remove the two normal stripe bands around the horizontal and vertical axes, as well as recombine the resultant four quadrants again. By using such a specific Fresnel concentrator design, a square light pattern can be constructed owing to the off-axis non-rotational symmetric superposition of light. In the second step, as for the response wavelengths of a specific triple-junction solar cell, we further carry out a triple-wavelength and multi-focus design of the above Fresnel concentrator for improving the uniformity of light distribution on the solar cell. To show the validity of this novel design method, a solar concentrator, with typical design parameters including the geometrical concentration ratio of 800× and the F-number of 0.775, is designed and simulated. As a result, theoretical irradiance uniformity up to 87% is obtained. In addition, considering the fact that no second optical element is involved in the concentrator system, our design method inherently has the advantages of good compactness, high efficiency, low cost, and ease for mass-production. We believe that such a concentrator is of great significance to solar cells for high conversion efficiency of light in the concentrator photovoltaic system. ? 2019 Optical Society of America.Accession Number: 20192807164239 -
Record 617 of
Title:High-speed focusing and scanning light through a multimode fiber based on binary amplitude-only modulation parallel coordinate algorithm
Author(s):Geng, Yi(1,3); Zhao, Guangzhi(1,3); Chen, Hui(1,3); Xu, Chengfang(1,3); Zhuang, Bin(1,3); Ren, Liyong(1,2)Source: Applied Physics B: Lasers and Optics Volume: 125 Issue: 5 DOI: 10.1007/s00340-019-7197-9 Published: May 1, 2019Abstract:In this paper, we present a binary amplitude-only modulation parallel coordinate algorithm for focusing and scanning light through a multimode fiber (MMF) based on the digital micro-mirror device (DMD) in a reference-free multimode fiber imaging system. In principle, our algorithm is capable of efficiently calculating the masks to be added to DMD for yielding a series of tightly focused spots; and for the same number of modulation sub-regions, our method is more than M (the number of focused spots) times faster than the amplitude iterative optimization algorithm. In the experiment, efficient light focusing and scanning at the distal end of the MMF are demonstrated. Furthermore, we demonstrate that the proposed method can also be extended to focus and scan light at multiple planes along the axial direction by just modifying the input wavefront accordingly; and our algorithm can be applied not only in multimode optical fiber focusing but also to other disordered media. Particularly, it will be valuable in fast multimode fiber calibration for endoscopic imaging. ? 2019, Springer-Verlag GmbH Germany, part of Springer Nature.Accession Number: 20191806862559 -
Record 618 of
Title:Photoacoustic Spectrometric Evaluation of Soil Heavy Metal Contaminants
Author(s):Liu, Lixian(1,3); Huan, Huiting(1); Zhang, Ming(1); Shao, Xiaopeng(1); Zhao, Binxing(2); Cui, Xinxin(3); Zhu, Lei(1)Source: IEEE Photonics Journal Volume: 11 Issue: 2 DOI: 10.1109/JPHOT.2019.2904295 Published: April 2019Abstract:Heavy metal pollution in soil has severe impact on the human health and global environment. There is an urgent need for cost-effective devices capable of recognizing and detecting heavy metallic matters in soils. A broadband photoacoustic spectrometric (PAS) system was established for the detection of heavy metal contaminants in soil. The heavy metal element lead (Pb) was selected as a preferred detection target. The near infrared photoacoustic spectra of contaminated soil samples with various concentrations of Pb were collected and the spectroscopic relationship between the soil absorption peaks and Pb concentrations was analyzed. Four advanced spectral preprocessing methods were explored to improve the robustness of the prediction model. Based on the maximal correlation coefficient and minimal root mean square error criteria of prediction, a two-layer feed-forward network with a continuum removing preprocessing method with a correlation coefficient as 0.96 was tested as the most appropriate method for Pb concentration prediction. This fact verifies that the broadband PAS evaluation methodology, as a nondestructive testing method, can be potentially used as an alternative quantification detection method of heavy metal contaminants in soil without the involvement of complicated sample pretreatment. ? 2009-2012 IEEE.Accession Number: 20191406737924 -
Record 619 of
Title:Observation of laser-cavity solitons in micro-resonators
Author(s):Bao, Hualong(1); Cooper, Andrew(1); Rowley, Maxwell(1); Di Lauro, Luigi(1); Gongora, Juan Sebastian Totero(1); Chu, Sai T.(2); Little, Brent E.(3); Oppo, Gian-Luca(4); Morandotti, Roberto(5,6,7); Moss, David J.(8); Wetzel, Benjamin(1,9); Peccianti, Marco(1); Pasquazi, Alessia(1)Source: Optics InfoBase Conference Papers Volume: Part F143-EQEC 2019 Issue: DOI: null Published: 2019Abstract:Optical frequency combs based on micro-cavity resonators, also known as 'micro-combs', are ready to achieve the full capability of their bulk counterparts but on an integrated footprint [1]. They have enabled major breakthroughs in spectroscopy, communications, microwave photonics, frequency synthesis, optical ranging, quantum sources and metrology. Of particular relevance was the recent experimental implementation of temporal cavity-solitons [2,3]. Temporal cavity-solitons in micro-resonators are described by the well-known Lugiato-Lefever equation. Currently, these self-localised waves form on top of a strong background of radiation, usually containing 95% of the total power [4] and require active control of an external driving laser - a complex process which limits the choice of fundamental parameters such as the repetition-rate. Developing simple methods for controlling and generating highly efficient, self-localised pulses is one of the most compelling challenges to overcome, in anticipation of the widespread use of micro-combs outside of laboratory environments. ? 2019 IEEEAccession Number: 20202008662942 -
Record 620 of
Title:Near-infrared carbon-implanted waveguides in Tb3+-doped aluminum borosilicate glasses
Author(s):Wang, Yue(1); Zhao, Jiaxin(1); Zhu, Qifeng(1); Shen, Jianping(1); Wang, Zhongyue(1); Guo, Hai-Tao(2); Liu, Chunxiao(1)Source: Frontiers of Optoelectronics Volume: 12 Issue: 4 DOI: 10.1007/s12200-019-0869-6 Published: December 1, 2019Abstract:Ion implantation has played a unique role in the fabrication of optical waveguide devices. Tb3+-doped aluminum borosilicate (TDAB) glass has been considered as an important magneto-optical material. In this work, near-infrared waveguides have been manufactured by the (5.5 + 6.0) MeV C3+ ion implantation with doses of (4.0 + 8.0) × 1013 ions·cm-2 in the TDAB glass. The modes propagated in the TDAB glass waveguide were recorded by a prism-coupling system. The finite-difference beam propagation method (FD-BPM) was carried out to simulate the guiding characteristics of the TDAB glass waveguide. The TDAB glass waveguide allows the light propagation with a single-mode at 1.539 μm and can serve as a potential candidate for future waveguide isolators. ? 2019, Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature.Accession Number: 20192006914349 -
Record 621 of
Title:Collect and select: Semantic alignment metric learning for few-shot learning
Author(s):Hao, Fusheng(1,2); He, Fengxiang(3); Cheng, Jun(1,2); Wang, Lei(1,2); Cao, Jianzhong(4); Tao, Dacheng(3)Source: Proceedings of the IEEE International Conference on Computer Vision Volume: 2019-October Issue: DOI: 10.1109/ICCV.2019.00855 Published: October 2019Abstract:Few-shot learning aims to learn latent patterns from few training examples and has shown promises in practice. However, directly calculating the distances between the query image and support image in existing methods may cause ambiguity because dominant objects can locate anywhere on images. To address this issue, this paper proposes a Semantic Alignment Metric Learning (SAML) method for few-shot learning that aligns the semantically relevant dominant objects through a ''collect-and-select'' strategy. Specifically, we first calculate a relation matrix (RM) to ''collect' the distances of each local region pairs of the 3D tensor extracted from a query image and the mean tensor of the support images. Then, the attention technique is adapted to ''select' the semantically relevant pairs and put more weights on them. Afterwards, a multi-layer perceptron (MLP) is utilized to map the reweighted RMs to their corresponding similarity scores. Theoretical analysis demonstrates the generalization ability of SAML and gives a theoretical guarantee. Empirical results demonstrate that semantic alignment is achieved. Extensive experiments on benchmark datasets validate the strengths of the proposed approach and demonstrate that SAML significantly outperforms the current state-of-the-art methods. The source code is available at https://github.com/haofusheng/SAML. ? 2019 IEEE.Accession Number: 20201208327056 -
Record 622 of
Title:Direct observation and characterization of optical guiding of microparticles by tightly focused non-diffracting beams
Author(s):Liang, Yansheng(1); Yan, Shaohui(2); Yao, Baoli(2); Lei, Ming(1,2)Source: Optics Express Volume: 27 Issue: 26 DOI: 10.1364/OE.381969 Published: 2019Abstract:Due to the propagation-invariant and self-healing properties, nondiffracting beams are highly attractive in optical trapping. However, little attention has been paid to investigating optical guiding of microparticles in nondiffracting beams generated by high-numerical-aperture (NA) optics with direct visualization. In this letter, we report a technique for direct observation and characterization of optical guiding of microparticles in a tight focusing system. With this technique, we observed a parabolic particle guiding trajectory with a longitudinal distance of more than 100μm and a maximal lateral deviation of 20 μm when using Airy beams. We also realized the tilted-path transport of microparticles with controllable guiding direction using tilted zeroth-order quasi-Bessel beams. For an NA of the focusing lens equal to 0.95, we achieved the optical guiding of microparticles along a straight path with a tilt angle of up to 18.8° with respect to the optical axis over a distance of 300 μm. Importantly, quantitative measurement of particle’s motion was readily accessed by measuring the particle’s position and velocity during the transport process. The reported technique for direct visualization and characterization of the guided particles will find its potential applications in optical trapping and guiding with novel nondiffracting beams or accelerating beams. ? 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement.Accession Number: 20200107978518 -
Record 623 of
Title:Dimensionality reduction based on PARAFAC model
Author(s):Yan, Ronghua(1); Peng, Jinye(2); Ma, Dongmei(3)Source: Journal of Imaging Science and Technology Volume: 63 Issue: 6 DOI: 10.2352/J.ImagingSci.Technol.2019.63.6.060501 Published: 2019Abstract:In hyperspectral image analysis, dimensionality reduction is a preprocessing step for hyperspectral image (HSI) classification. Principal component analysis (PCA) reduces the spectral dimension and does not utilize the spatial information of an HSI. To solve it, the tensor decompositions have been successfully applied to joint noise reduction in spatial and spectral dimensions of hyperspectral images, such as parallel factor analysis (PARAFAC). However, the PARAFAC method does not reduce the dimension in the spectral dimension. To improve it, two new methods were proposed in this article, that is, combine PCA and PARAFAC to reduce both the dimension in the spectral dimension and the noise in the spatial and spectral dimensions. The experimental results indicate that the new methods improve the classification compared with the PARAFAC method. ? Society for Imaging Science and Technology 2019Accession Number: 20200608131396 -
Record 624 of
Title:Efficient light focusing through an MMF based on two-step phase shifting and parallel phase compensating
Author(s):Chen, Hui(1,3); Geng, Yi(1,3); Xu, Chengfang(1,3); Zhuang, Bin(1,3); Ju, Haijuan(1,3); Ren, Liyong(1,2)Source: Applied Optics Volume: 58 Issue: 27 DOI: 10.1364/AO.58.007552 Published: September 20, 2019Abstract:Based on a parallel phase compensation scheme, we propose an efficient wavefront shaping method using a spatial light modulator (SLM) for quickly generating a series of focused spots through a multimode fiber (MMF). The compensated phase mask obtained by a two-step phase-shifting technique is loaded to the SLM for generating a focused spot at an arbitrary target position out of the fiber facet. Furthermore, the parallel algorithm we present makes it possible to obtain a series of compensated phase masks, which could be used to generate a series of focused spots at different locations. We experimentally obtained 100 tightly focused spots, with an average focused efficiency of 21.60% and an average focused diameter of 1.9240 μm, and only one-time parallel-compensated phase retrieval is required without multiple iteration optimization. ? 2019 Optical Society of America.Accession Number: 20193907463002