2016

• Record 241 of
  
  Title:Optical waveguides in magneto-optical glasses fabricated by proton implantation
  
  Author(s):Liu, Chun-Xiao(1); Li, Yu-Wen(1); Zheng, Rui-Lin(1); Fu, Li-Li(2); Zhang, Liao-Lin(1); Guo, Hai-Tao(3); Zhou, Zhi-Guang(3); Li, Wei-Nan(3); Lin, She-Bao(4); Wei, Wei(1)
  Source: Optics and Laser Technology  Volume: 85  Issue:   DOI: 10.1016/j.optlastec.2016.05.008  Published: November 1, 2016  
  Abstract:Planar waveguides in magneto-optical glasses (Tb3+-doped aluminum borosilicate glasses) have been produced by a 550-keV proton implantation at a dose of 4.0×1016 ions/cm2 for the first time to our knowledge. After annealing at 260 °C for 1.0 h, the dark-mode spectra and near-field intensity distributions are measured by the prism-coupling and end-face coupling methods. The damage profile, refractive index distribution and light propagation mode of the planar waveguide are numerically calculated by SRIM 2010, RCM and FD-BPM, respectively. The effects of implantation on the structural and optical properties are investigated by Raman and absorption spectra. It suggests that the proton-implanted Tb3+-doped aluminum borosilicate glass waveguide is a good candidate for a waveguide isolator in optical fiber communication and all-optical communication. © 2016 Elsevier Ltd All rights reserved.
  Accession Number: 20162602536533
• Record 242 of
  
  Title:Modified photon counting communication method for underwater application
  
  Author(s):Han, Biao(1,2); Zhao, Wei(1); Wang, Wei(1); Su, Yulong(1); Liu, Jifang(3)
  Source: Guangxue Xuebao/Acta Optica Sinica  Volume: 36  Issue: 8  DOI: 10.3788/AOS201636.0806004  Published: August 10, 2016  
  Abstract:Underwater laser communication is influenced by the absorption and scattering of water, which causes severe signal energy attenuation during propagation. Laser communication based on the photon counting is considered as an effective way to resist signal loss and increase communication distance because of its ultra-high detection sensitivity. However, since communication data recovery is usually realized by detecting electrical pulse at the output of single photon detector directly in traditional photon counting communication, the communication bit error rate would be easily influenced by background light noise. In this paper, an improved method is proposed and studied to solve this problem. In our approach, the photons arrived at the communication receiver are converted into electrical pulses by single photon detector first. Then, communication data is recovered through counting the electrical pulse number on unit time. The experimental result shows that detection sensitivity of 84.24 bit-1 can be realized by the proposed method, when the communication wavelength is 532 nm, the communication rate is 50 kb/s, and the signal to noise ratio is 5.14.The novel approach proposed in this paper provides a new technical idea for high-sensitivity underwater laser communication. © 2016, Chinese Lasers Press. All right reserved.
  Accession Number: 20163702800339
• Record 243 of
  
  Title:Hyperspectral image classification via multitask joint sparse representation and stepwise MRF optimization
  
  Author(s):Yuan, Yuan(1); Lin, Jianzhe(1); Wang, Qi(2)
  Source: IEEE Transactions on Cybernetics  Volume: 46  Issue: 10  DOI: 10.1109/TCYB.2015.2484324  Published: October 15, 2015  
  Abstract:Hyperspectral image (HSI) classification is a crucial issue in remote sensing. Accurate classification benefits a large number of applications such as land use analysis and marine resource utilization. But high data correlation brings difficulty to reliable classification, especially for HSI with abundant spectral information. Furthermore, the traditional methods often fail to well consider the spatial coherency of HSI that also limits the classification performance. To address these inherent obstacles, a novel spectral-spatial classification scheme is proposed in this paper. The proposed method mainly focuses on multitask joint sparse representation (MJSR) and a stepwise Markov random filed framework, which are claimed to be two main contributions in this procedure. First, the MJSR not only reduces the spectral redundancy, but also retains necessary correlation in spectral field during classification. Second, the stepwise optimization further explores the spatial correlation that significantly enhances the classification accuracy and robustness. As far as several universal quality evaluation indexes are concerned, the experimental results on Indian Pines and Pavia University demonstrate the superiority of our method compared with the state-of-the-art competitors. © 2015 IEEE.
  Accession Number: 20154301434275
• Record 244 of
  
  Title:Speckle-correlation microscopic imaging through scattering medium
  
  Author(s):Zhou, Meiling(1,2); Singh, Alok Kumar(1); Pedrini, Giancarlo(1); Osten, Wolfgang(1); Yao, Baoli(2)
  Source: Optics InfoBase Conference Papers  Volume:   Issue:   DOI: 10.1364/DH.2016.DT1E.2  Published: July 18, 2016  
  Abstract:In this paper we are presenting a non-invasive and lensless method to utilize a scattering media for microscopic imaging. Thanks to its lens-like property, we can adjust the magnification and resolution of the system and reconstruct the microscopic object using phase retrieval technique from the autocorrelation of a single-shot speckle intensity distribution. © OSA 2016.
  Accession Number: 20171303511622
• Record 245 of
  
  Title:Surveillance video synopsis via scaling down objects
  
  Author(s):Li, Xuelong(1); Wang, Zhigang(2); Lu, Xiaoqiang(1)
  Source: IEEE Transactions on Image Processing  Volume: 25  Issue: 2  DOI: 10.1109/TIP.2015.2507942  Published: February 1, 2016  
  Abstract:Video synopsis is an effective technique to provide a compact representation of the original video by removing spatiotemporal redundancies and by preserving the essential activities. Most current approaches for video synopsis will cause collisions among objects, especially when the video is condensed much. In this paper, we present an approach for video synopsis to reduce the collisions. Our approach first shifts active objects along the time axis to compact the original video. Then, the sizes of the objects are reduced when collisions occur. Meanwhile, the geometric centroids of the objects will be kept unchanged to preserve the location information. Our contributions are threefold. First, an approach is proposed to decrease collisions in the synopsis video through reducing the sizes of the objects. Second, an optimization framework is developed to indicate the optimal time position and the appropriate reduction coefficient for each object. Finally, some metrics are proposed, and several experiments are carried out to evaluate the proposed approach. The experiments have demonstrated that the synopsis video produced by our approach has much fewer collisions while the compression ratio is high. © 2015 IEEE.
  Accession Number: 20163302707696
• Record 246 of
  
  Title:Wideband slow-light propagation with no distortion in a nanofiber-plane-grating composite waveguide
  
  Author(s):Ma, Chengju(1); Ren, Liyong(2); Guo, Wenge(1); Fu, Haiwei(1); Xu, Yiping(3); Liu, Yinggang(1); Zhang, Xiaozhen(1)
  Source: Optical Engineering  Volume: 55  Issue: 6  DOI: 10.1117/1.OE.55.6.066120  Published: June 1, 2016  
  Abstract:A nanofiber-plane-grating composite slow-light waveguide to achieve wideband slowlight propagation with no distortion is proposed. The waveguide is formed by embedding a tapered nanofiber into a V-groove on a plane-grating surface. By optimizing the waveguide structural parameters, a slow-light effect with bandwidth of about 1453 GHz is obtained. Based on finite-difference time-domain (FDTD) method, we analyze the waveguide's optical properties and slow-light characteristics. Simulation results show that a picosecond optical pulse propagating in the slow-light waveguide can be delayed for about 980 fs and without distortion. The group velocity of the optical pulse can be reduced to about 0.3c (c is the speed of light in vacuum). This study will provide important theoretical basis and innovative ideas for the development of new-Type slow-light elements. © 2016 Society of Photo-Optical Instrumentation Engineers (SPIE).
  Accession Number: 20162702569605
• Record 247 of
  
  Title:Online fabrication scheme of helical long-period fiber grating for liquid-level sensing
  
  Author(s):Ren, Kaili(1,2,3); Ren, Liyong(1); Liang, Jian(1,3); Kong, Xudong(1,3); Ju, Haijuan(1); Xu, Yiping(1,3); Wu, Zhaoxin(2)
  Source: Applied Optics  Volume: 55  Issue: 34  DOI: 10.1364/AO.55.009675  Published: December 1, 2016  
  Abstract:We present a novel online fabrication scheme of helical long-period fiber gratings (H-LPFGs) by directly twisting a standard single-mode fiber (SMF) in a microheater. This is done by taking advantage of the inherent core-cladding eccentricity in SMF. We adopt a fiber optic rotary joint to eliminate the accompanying twisting spiral for real-time spectral monitoring and a stepping mechanical system to accurately control the twisting length in fabrication. As a consequence, low-cost and high-quality H-LPFGs can be readily fabricated. Meanwhile, by using this kind of H-LPFG, we design a simple and low-cost wavelength-interrogated liquid-level sensor with a high sensitivity of 0.1 nm/mm. © 2016 Optical Society of America.
  Accession Number: 20165103148244
• Record 248 of
  
  Title:Unsupervised 3D Local Feature Learning by Circle Convolutional Restricted Boltzmann Machine
  
  Author(s):Han, Zhizhong(1); Liu, Zhenbao(1); Han, Junwe(1); Vong, Chi-Man(2); Bu, Shuhui(1); Li, Xuelong(3)
  Source: IEEE Transactions on Image Processing  Volume: 25  Issue: 11  DOI: 10.1109/TIP.2016.2605920  Published: November 2016  
  Abstract:Extracting local features from 3D shapes is an important and challenging task that usually requires carefully designed 3D shape descriptors. However, these descriptors are hand-crafted and require intensive human intervention with prior knowledge. To tackle this issue, we propose a novel deep learning model, namely circle convolutional restricted Boltzmann machine (CCRBM), for unsupervised 3D local feature learning. CCRBM is specially designed to learn from raw 3D representations. It effectively overcomes obstacles such as irregular vertex topology, orientation ambiguity on the 3D surface, and rigid or slightly non-rigid transformation invariance in the hierarchical learning of 3D data that cannot be resolved by the existing deep learning models. Specifically, by introducing the novel circle convolution, CCRBM holds a novel ring-like multi-layer structure to learn 3D local features in a structure preserving manner. Circle convolution convolves across 3D local regions via rotating a novel circular sector convolution window in a consistent circular direction. In the process of circle convolution, extra points are sampled in each 3D local region and projected onto the tangent plane of the center of the region. In this way, the projection distances in each sector window are employed to constitute a novel local raw 3D representation called projection distance distribution (PDD). In addition, to eliminate the initial location ambiguity of a sector window, the Fourier transform modulus is used to transform the PDD into the Fourier domain, which is then conveyed to CCRBM. Experiments using the learned local features are conducted on three aspects: global shape retrieval, partial shape retrieval, and shape correspondence. The experimental results show that the learned local features outperform other state-of-the-art 3D shape descriptors. © 2016 IEEE.
  Accession Number: 20173404058857
• Record 249 of
  
  Title:Two-Stage Learning to Predict Human Eye Fixations via SDAEs
  
  Author(s):Han, Junwei(1); Zhang, Dingwen(1); Wen, Shifeng(1); Guo, Lei(1); Liu, Tianming(2); Li, Xuelong(3)
  Source: IEEE Transactions on Cybernetics  Volume: 46  Issue: 2  DOI: 10.1109/TCYB.2015.2404432  Published: February 2016  
  Abstract:Saliency detection models aiming to quantitatively predict human eye-Attended locations in the visual field have been receiving increasing research interest in recent years. Unlike traditional methods that rely on hand-designed features and contrast inference mechanisms, this paper proposes a novel framework to learn saliency detection models from raw image data using deep networks. The proposed framework mainly consists of two learning stages. At the first learning stage, we develop a stacked denoising autoencoder (SDAE) model to learn robust, representative features from raw image data under an unsupervised manner. The second learning stage aims to jointly learn optimal mechanisms to capture the intrinsic mutual patterns as the feature contrast and to integrate them for final saliency prediction. Given the input of pairs of a center patch and its surrounding patches represented by the features learned at the first stage, a SDAE network is trained under the supervision of eye fixation labels, which achieves both contrast inference and contrast integration simultaneously. Experiments on three publically available eye tracking benchmarks and the comparisons with 16 state-of-The-Art approaches demonstrate the effectiveness of the proposed framework. © 2013 IEEE.
  Accession Number: 20150900590265
• Record 250 of
  
  Title:Design and research of moving objects dimension measurement system based on linear array CCD
  
  Author(s):Lei, Fanpu(1,2,3); Bai, Yonglin(3); Zhu, Bingli(3)
  Source: Proceedings of SPIE - The International Society for Optical Engineering  Volume: 10154  Issue:   DOI: 10.1117/12.2246493  Published: 2016  
  Abstract:A novel moving objects dimension measurement system based on the linear array CCD is designed. The light source is a pulsed laser with pulse width 200ns. Single point of light passes through lens converted to parallel light which will illuminate to the CCD through the moving object to be tested. CCD pixels which are blocked by the object while light is on are low, and the remaining pixels are high conversely. The distance of the tested objects while light is on can be ignored since the light pulse width is much smaller than the integration time of CCD (generally). The size of the tested object can be achieved by the number of dark pixels of CCD while light is on. This paper introduces the principle and composition of the dimension measurement system. The results show that this system can measure the size of moving objects and measuring accuracy is better than 50 microns. Accuracy and stability of the system can achieve actual production requirements when the object's moving speed is smaller than 50mm/s. Optimizing the parallelism of the parallel light, the measurement accuracy can be further improved. © 2016 SPIE.
  Accession Number: 20170503310073
• Record 251 of
  
  Title:Classifying Discriminative Features for Blur Detection
  
  Author(s):Pang, Yanwei(1); Zhu, Hailong(1); Li, Xinyu(1); Li, Xuelong(2)
  Source: IEEE Transactions on Cybernetics  Volume: 46  Issue: 10  DOI: 10.1109/TCYB.2015.2472478  Published: October 2016  
  Abstract:Blur detection in a single image is challenging especially when the blur is spatially-varying. Developing discriminative blur features is an open problem. In this paper, we propose a new kernel-specific feature vector consisting of the information of a blur kernel and the information of an image patch. Specifically, the kernel specific-feature is composed of the multiplication of the variance of filtered kernel and the variance of filtered patch gradients. The feature origins from a blur-classification theorem and its discrimination can also be intuitively explained. To make the kernel-specific features useful for real applications, we build a pool of kernels consisting of motion-blur kernels, defocus-blur (out-of-focus) kernels, and their combinations. By extracting such features followed by the classifiers, the proposed algorithm outperforms the state-of-the-art blur detection method. Experimental results on public databases demonstrate the effectiveness of the proposed method. © 2015 IEEE.
  Accession Number: 20153701272188
• Record 252 of
  
  Title:Watts-level super-compact narrow-linewidth Tm-doped silica all-fiber laser near 1707 nm with fiber Bragg gratings
  
  Author(s):Xiao, X.S.(1,2); Guo, H.T.(1); Lu, M.(1); Yan, Z.J.(1); Wang, H.S.(1); Wang, Y.S.(1); Xu, Y.T.(1); Gao, C.X.(1); Cui, X.X.(1); Guo, Q.(1,2); Peng, B.(1)
  Source: Laser Physics  Volume: 26  Issue: 11  DOI: 10.1088/1054-660X/26/11/115103  Published: November 2016  
  Abstract:Watts-level ultra-short wavelength operation of a Tm-doped all fiber laser was developed by using a 1550 nm Er-doped fiber laser pump source and a pair of fiber Bragg gratings (FBGs). The laser yielded 1.28 W of continuous-wave output at 1707.01 nm with a narrow linewidth of ∼44 pm by means of a 20 cm Tm-doped fiber. The dependencies of the slope efficiencies and pump threshold of the Tm-doped fiber laser versus the length of active fiber and reflectivity of the output mirror (FBG) were investigated in detail, in which the maximum average slope efficiency was 36.1%. There is no doubt that this all fiber laser will be a perfect pump source for mid-IR laser output. © 2016 Astro Ltd.
  Accession Number: 20164703047835