2013
2013
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Record 349 of
Title:Watt-level passively Q-switched double-cladding fiber laser based on graphene oxide saturable absorber
Author(s):Yu, Zhenhua(1); Song, Yanrong(1); Dong, Xinzheng(1); Li, Yanlin(1); Tian, Jinrong(1); Wang, Yonggang(2)Source: Applied Optics Volume: 52 Issue: 29 DOI: 10.1364/AO.52.007127 Published: October 10, 2013Abstract:A watt-level passively Q-switched ytterbium-doped double-cladding fiber laser with a graphene oxide (GO) absorber was demonstrated. The structure of the GO saturable absorber mirror (GO-SAM) was of the sandwich type. A maximum output power of 1.8 W was obtained around a wavelength of 1044 nm. To the best of our knowledge, this is the highest output power in Q-switched fiber lasers based on a GO saturable absorber. The pure GO was protected from the oxygen in the air so that the damage threshold of the GO-SAM was effectively raised. The gain fiber was a D-shaped ytterbium-doped doublecladding fiber. The pulse repetition rates were tuned from 120 to 215 kHz with pump powers from 3.89 to 7.8 W. The maximum pulse energy was 8.37 μJ at a pulse width of 1.7 μs. ? 2013 Optical Society of America.Accession Number: 20134316904298 -
Record 350 of
Title:Image registration by normalized mapping
Author(s):Wang, Qi(1,2); Zou, Cuiming(3); Yuan, Yuan(1); Lu, Hongbing(4); Yan, Pingkun(1)Source: Neurocomputing Volume: 101 Issue: DOI: 10.1016/j.neucom.2012.08.012 Published: February 4, 2013Abstract:A new non-rigid registration method is proposed for the bladder magnetic resonance (MR) images. The key point is normalized mapping, which transforms any image into an intermediate space. Under the uniform space, those anatomical feature points of different images are corresponded by rotating and scaling. In addition, the non-rigid registration is utilized under the application of groupwise registration. By registering a set of images, an unbiased template can be obtained. Based on this template, the analysis towards the group of images can be easily conducted. Experimental results demonstrate that the proposed method can register accurately the target image to the reference image. ? 2012 Elsevier B.V.Accession Number: 20124615668524 -
Record 351 of
Title:A 1319nm diode-side-pumped Nd:YAG laser Q-switched with graphene oxide
Author(s):Zhang, Ling(1); Yu, Haijuan(1); Yan, Shilian(1); Zhao, Weifang(1); Sun, Wei(1); Yang, Yingying(1); Wang, Lirong(1); Hou, Wei(1); Lin, Xuechun(1); Wang, Yonggang(2); Wang, Yishan(2)Source: Journal of Modern Optics Volume: 60 Issue: 15 DOI: 10.1080/09500340.2013.837975 Published: 2013Abstract:We have demonstrated a diode-side-pumped Q-switched Nd:YAG laser operating at 1319 nm with a saturable absorber of graphene oxide fabricated by the vertical evaporation method. The 1319 nm Q-switched laser pulses were realized with average output power of 820 mW, pulse width of 2 μs and repetition rate of 35 kHz. The pulse energy and peak power were 23.4 μJ and 11.7W, respectively when the optical pump power was 232W. The experimental results indicate that graphene oxide is an effective saturable absorber for Q-switched lasers. ? 2013 Taylor & Francis.Accession Number: 20134817038443 -
Record 352 of
Title:Mode locked Er-doped f iber laser with single-wall carbon nanotube saturable absorber
Author(s):Yu, Zhenhua(1); Song, Yanrong(1); Dong, Xinzheng(1); Tian, Jinrong(1); Wang, Yonggang(2)Source: Chinese Optics Letters Volume: 11 Issue: SUPPL.2 DOI: 10.3788/COL201311.S21403 Published: 2013Abstract:A mode locked Er-doped fiber laser based on a single-wall carbon nanotube saturable absorber is demonstrated. A high quality single-wall carbon nanotubes (SWCNTs) absorber film is fabricated by a polymer composite. The pulse duration is 488 fs with 9.6-nm spectral width at the center of 1564 nm. The repetition rate is 30.4 MHz. The maximum output power is 3 mW. And the single pulse energy is 0.1 nJ. ? 2013 Chinese Optics Letters.Accession Number: 20141117464276 -
Record 353 of
Title:Passive Q-switching in a diode-side-pumped Nd:YAG laser at 1.319 μ m
Author(s):Yan, Shilian(1); Zhang, Ling(1); Yu, Haijuan(1); Li, Menglong(1); Sun, Wei(1); Hou, Wei(1); Lin, Xuechun(1); Wang, Yonggang(2); Wang, Yishan(2)Source: Optical Engineering Volume: 52 Issue: 10 DOI: 10.1117/1.OE.52.10.106107 Published: 2013Abstract:We demonstrated a passively Q-switched Nd:YAG laser operating at 1.319 μm using a transmission-type single-wall carbon nanotube (SWCNT) as the saturable absorber. This is the first report on using SWCNT as a Q-switcher for 1.319 μm Nd:YAG laser in a side-pumped configuration. A maximum output power of 780 mW was obtained with 1.15-μs pulse duration and 42.7-kHz repetition rate. ? 2013 Society of Photo-Optical Instrumentation Engineers.Accession Number: 20134516950204 -
Record 354 of
Title:Intrinsic image decomposition using optimization and user scribbles
Author(s):Shen, Jianbing(1); Yang, Xiaoshan(1); Li, Xuelong(2); Jia, Yunde(1)Source: IEEE Transactions on Cybernetics Volume: 43 Issue: 2 DOI: 10.1109/TSMCB.2012.2208744 Published: April 2013Abstract:In this paper, we present a novel high-quality intrinsic image recovery approach using optimization and user scribbles. Our approach is based on the assumption of color characteristics in a local window in natural images. Ourmethod adopts a premise that neighboring pixels in a local window having similar intensity values should have similar reflectance values. Thus, the intrinsic image decomposition is formulated by minimizing an energy function with the addition of a weighting constraint to the local image properties. In order to improve the intrinsic image decomposition results, we further specify local constraint cues by integrating the user strokes in our energy formulation, including constant-reflectance, constant-illumination, and fixed-illumination brushes. Our experimental results demonstrate that the proposed approach achieves a better recovery result of intrinsic reflectance and illumination components than the previous approaches. ? 2012 IEEE.Accession Number: 20135117116102 -
Record 355 of
Title:Spectroscopic properties and Judd-Ofelt analysis of Dy3+-doped and Dy3+, Tm3+-codped Ge-In-S chalcogenide glasses
Author(s):Guo, Haitao(1); Xu, Yantao(1); Chen, Hongyan(2); Cui, Xiaoxia(1); Qiao, Zebang(1); Gu, Shaoxuan(3); Hou, Chaoqi(1); Meng, Wei(1); Lu, Chunfeng(1); Peng, Bo(1)Source: Journal of Non-Crystalline Solids Volume: 377 Issue: DOI: 10.1016/j.jnoncrysol.2013.01.013 Published: 2013Abstract:0.2 wt.% Dy3+-doped and 0.2 wt.% Dy3+, 0.5 wt.% Tm3+-codoped (100-x)GeS2·xIn2S 3 (x=5,10,15,20,25) chalcogenide glasses were prepared. Their spectroscopic properties were analyzed based on absorption (ranges from 500 to 3000 nm) and emission (ranges from 1000 to 4700 nm) measurements. The Judd-Ofelt strength parameters Ωt (t =2, 4, 6) and the spectroscopy parameters Arad, β and τrad were calculated, and the σemi of the 1330, 2930 and 4320 nm fluorescences were estimated. These Dy3+-doped and Dy3+, Tm 3+-codoped Ge-In-S chalcogenide glasses are valuable materials for using in 1.3 μm fiber-amplifiers and 2-5 μm mid-infrared laser devices. ? 2013 Elsevier B.V. All rights reserved.Accession Number: 20133916773068 -
Record 356 of
Title:Performance of the detection system for X-ray pulsar based navigation
Author(s):Sheng, Li-Zhi(1,2); Zhao, Bao-Sheng(1); Zhou, Feng(1); Wang, Peng(1); Song, Juan(1,2); Liu, Yong-An(1); Shen, Jing-Shi(3); Hu, Hui-Jun(3); Ma, Xiao-Fei(1,2)Source: Guangzi Xuebao/Acta Photonica Sinica Volume: 42 Issue: 9 DOI: 10.3788/gzxb20134209.1071 Published: September 2013Abstract:In order to assess the performance of detection system for X-ray pulsar navigation, the expression of the signal-to-noise ratio (SNR) and the minimum detectable power are derived in the photon counting mode of the system. Experiment system to measure the SNR and the minimum detectable power is setup. The minimum detectable power is measured; the SNRs at different integration time, optical power and threshold voltage are calculated. The X-ray pulse profile is reconstructed by measuring the time of arrival (TOA) of the X-ray photons. Experimental results show that the SNR of the pulse profile is improved and the curve of the pulse profile tends to smooth with the increasing of optical power and the integration time; the SNR is 26.3 and the pulse profile is optimal when the threshold voltage is -150 mV; the minimum detectable power of the system is 3.5×10-16 W.Accession Number: 20134216860614 -
Record 357 of
Title:Slow feature analysis for multi-camera activity understanding
Author(s):Zhang, Lei(1,2); Lu, Xiaoqiang(1); Yuan, Yuan(1)Source: Proceedings - 2013 International Conference on Virtual Reality and Visualization, ICVRV 2013 Volume: Issue: DOI: 10.1109/ICVRV.2013.46 Published: 2013Abstract:Multi-camera activity analysis is a key point in video surveillance of many wide-area scenes, such as airports, underground stations, shopping mall and road junctions. On the basis of previous work, this paper presents a new feature learning method based on Slow Feature Analysis (SFA) to understand activities observed across the network of cameras. The main contribution of this paper can be summarized as follows: (1) It is the first time that SFA-based learning method is introduced to multi-camera activity understanding; (2) It presents an evaluation to examine the effectiveness of SFA-based method to facilitate the learning of inter-camera activity pattern dependencies; and (3) It estimates the sensitivity of learning inter-camera time delayed dependency given different training size, which is a critical factor for accurate dependency learning and has not been largely studied by existing work before. Experiments are carried out on a dataset obtained in a trident roadway. The results demonstrate that the SFA-based method outperforms the sate of the art. ? 2013 IEEE.Accession Number: 20140717300082 -
Record 358 of
Title:Biview face recognition in the shape-texture domain
Author(s):Xiao, Bing(1,2); Gao, Xinbo(1); Tao, Dacheng(3); Li, Xuelong(4)Source: Pattern Recognition Volume: 46 Issue: 7 DOI: 10.1016/j.patcog.2012.12.009 Published: July 2013Abstract:Face recognition is one of the biometric identification methods with the highest potential. The existing face recognition algorithms relying on the texture information of face images are affected greatly by the variation of expression, scale and illumination. Whereas the algorithms based on the shape topology weaken the influence of illumination to some extent, but the impact of expression, scale and illumination on face recognition is still unsolved. To this end, we propose a new method for face recognition by integrating texture information with shape information, called biview face recognition algorithm. The texture models are constructed by using subspace learning methods and shape topologies are formed by building graphs for face images. The proposed biview face recognition method is compared with recognition algorithms merely based on texture or shape information. Experimental results of recognizing faces under the variation of illumination, expression and scale demonstrate that the performance of the proposed biview face recognition outperforms texture-based and shape-based algorithms. ? 2012 Elsevier Ltd. All rights reserved.Accession Number: 20131316148904 -
Record 359 of
Title:Person re-identification by regularized smoothing kiss metric learning
Author(s):Tao, Dapeng(1); Jin, Lianwen(1); Wang, Yongfei(1); Yuan, Yuan(2); Li, Xuelong(2)Source: IEEE Transactions on Circuits and Systems for Video Technology Volume: 23 Issue: 10 DOI: 10.1109/TCSVT.2013.2255413 Published: 2013Abstract:With the rapid development of the intelligent video surveillance (IVS), person re-identification, which is a difficult yet unavoidable problem in video surveillance, has received increasing attention in recent years. That is because computer capacity has shown remarkable progress and the task of person re-identification plays a critical role in video surveillance systems. In short, person re-identification aims to find an individual again that has been observed over different cameras. It has been reported that KISS metric learning has obtained the state of the art performance for person re-identification on the VIPeR dataset . However, given a small size training set, the estimation to the inverse of a covariance matrix is not stable and thus the resulting performance can be poor. In this paper, we present regularized smoothing KISS metric learning (RS-KISS) by seamlessly integrating smoothing and regularization techniques for robustly estimating covariance matrices. RS-KISS is superior to KISS, because RS-KISS can enlarge the underestimated small eigenvalues and can reduce the overestimated large eigenvalues of the estimated covariance matrix in an effective way. By providing additional data, we can obtain a more robust model by RS-KISS. However, retraining RS-KISS on all the available examples in a straightforward way is time consuming, so we introduce incremental learning to RS-KISS. We thoroughly conduct experiments on the VIPeR dataset and verify that 1) RS-KISS completely beats all available results for person re-identification and 2) incremental RS-KISS performs as well as RS-KISS but reduces the computational cost significantly. ? 1991-2012 IEEE.Accession Number: 20134316876221 -
Record 360 of
Title:Rank preserving sparse learning for kinect based scene classification
Author(s):Tao, Dapeng(1); Jin, Lianwen(1); Yang, Zhao(1); Li, Xuelong(2)Source: IEEE Transactions on Cybernetics Volume: 43 Issue: 5 DOI: 10.1109/TCYB.2013.2264285 Published: October 2013Abstract:With the rapid development of the RGB-D sensors and the promptly growing population of the low-cost Microsoft Kinect sensor, scene classification, which is a hard, yet important, problem in computer vision, has gained a resurgence of interest recently. That is because the depth of information provided by the Kinect sensor opens an effective and innovative way for scene classification. In this paper, we propose a new scheme for scene classification, which applies locality-constrained linear coding (LLC) to local SIFT features for representing the RGB-D samples and classifies scenes through the cooperation between a new rank preserving sparse learning (RPSL) based dimension reduction and a simple classification method. RPSL considers four aspects: 1) it preserves the rank order information of the within-class samples in a local patch; 2) it maximizes the margin between the between-class samples on the local patch; 3) the L1- norm penalty is introduced to obtain the parsimony property; and 4) it models the classification error minimization by utilizing the least-squares error minimization. Experiments are conducted on the NYU Depth V1 dataset and demonstrate the robustness and effectiveness of RPSL for scene classification. ? 2013 IEEE.Accession Number: 20135117116184