2017

• Record 373 of
  
  Title:Design and analysis of push-broom optical camera's following windows
  
  Author(s):Chen, Su(1); Wang, Hu(1); Xue, Yaoke(1); Liu, Meiying(1); Wang, Lingguang(1)
  Source: Proceedings of SPIE - The International Society for Optical Engineering  Volume: 10463  Issue:   DOI: 10.1117/12.2284267  Published: 2017  
  Abstract:In order to solve the problem of push-broom optical camera's imagery quality difficult to content request which windows size is too large, the author proposed a kind of project for camera's following windows. The author analysed the characteristic of the push-broom optical camera's windows, and proposed the ideal model of the push-broom optical camera's windows. Simultaneously, analyzed the transformational rule of the windows' location and size in the ideal condition. The author proposed the design project of the push-broom optical camera's following windows according to the result of the ideal windows' analysis, and performed an analysis of kinematics simultaneously. Finally, the author designed and analyzed kinematics for the following windows in allusion to a certain push-broom optical camera. According the analysis result, this project could decrease a half size of the light opening area compare with the current technique. It could decrease the stray light's influence of the camera's imagery quality, the following windows move smoothly, and this project could be satisfied to the requirements of engineering use. © 2017 SPIE.
  Accession Number: 20180304654851
• Record 374 of
  
  Title:Structural evolution study of additions of Sb2S3 and CdS into GeS2 chalcogenide glass by Raman spectroscopy
  
  Author(s):Guo, Hai-Tao(1,2); Zhang, Ming-Jie(1,3); Xu, Yan-Tao(2); Xiao, Xu-Sheng(2); Yang, Zhi-Yong(1)
  Source: Chinese Physics B  Volume: 26  Issue: 10  DOI: 10.1088/1674-1056/26/10/104208  Published: October 2017  
  Abstract:The structures of pseudo-binary GeS2Sb2S3, GeS2CdS, Sb2S3CdS, and pseudo-ternary GeS2Sb2S3CdS chalcogenide systems are systematically investigated by Raman spectroscopy. It is shown that a small number of [S3GeGeS3] structural units (SUs) and -S-S-/S8 groups exist simultaneously in GeS2 glass which has a three-dimensional continuous network backbone consisting of cross-linked corner-sharing and edge-sharing [GeS4] tetrahedra. When Sb2S3 is added into GeS2 glass, the network backbone becomes interconnected [GeS4] tetrahedra and [SbS3] pyramids. Moreover, Ge atoms in [S3GeGeS3] SUs tend to capture S atoms from Sb2S3, leading to the formation of [S2SbSbS2] SUs. When CdS is added into GeS3 glass, [Cd4GeS6] polyhedra are formed, resulting in a strong crystallization tendency. In addition, Ge atoms in [S3GeGeS3] SUs tend to capture S atoms from CdS, resulting in the dissolution of GeGe bond. Co-melting of Sb2S3 or CdS with GeS2 reduces the viscosity of the melt and improves the homogeneity of the glass. The GeS2 glass can only dissolve up to 10-mol% CdS without crystallization. In comparison, GeS2Sb2S3 glasses can dissolve up to 20-mol% CdS, implying that Sb2S3 could delay the construction of [Cd4GeS6] polyhedron and increase the dissolving amount of CdS in the glass. © 2017 Chinese Physical Society and IOP Publishing Ltd.
  Accession Number: 20174204273439
• Record 375 of
  
  Title:Optical uxes in coupled PT-symmetric photonic structures
  
  Author(s):Ge, Li(1,2); Makris, Konstantinos G.(3); Zhang, Lingxuan(1,4)
  Source: arXiv  Volume:   Issue:   DOI:   Published: June 15, 2017  
  Abstract:In this work we first examine transverse and longitudinal uxes in a PT -symmetric photonic dimer using a coupled-mode theory. Several surprising understandings are obtained from this perspective: The longitudinal ux shows that the PT transition in a dimer can be regarded as a classical effect, despite its analogy to PT -symmetric quantum mechanics. The longitudinal ux also indicates that the so-called giant amplification in the PT -symmetric phase is a sub-exponential behavior and does not outperform a single gain waveguide. The transverse ux, on the other hand, reveals that the apparent power oscillations between the gain and loss waveguides in the PT -symmetric phase can be deceiving in certain cases, where the transverse power transfer is in fact unidirectional. We also show that this power transfer cannot be arbitrarily fast even when the exceptional point is approached. Finally, we go beyond the coupled-mode theory by using the paraxial wave equation and also extend our discussions to a PT diamond and a one-dimensional periodic lattice. Copyright © 2017, The Authors. All rights reserved.
  Accession Number: 20200120497
• Record 376 of
  
  Title:Hyperspectral anomaly detection based on machine learning and building selection graph
  
  Author(s):Tang, Yehui(1); Qin, Hanlin(1); Liang, Ying(1); Leng, Hanbing(2); Ju, Zezhao(1)
  Source: Proceedings of SPIE - The International Society for Optical Engineering  Volume: 10462  Issue:   DOI: 10.1117/12.2285780  Published: 2017  
  Abstract:In hyperspectral images, anomaly detection without prior information develops rapidly. Most of the existing methods are based on restrictive assumptions of the background distribution. However, the complexity of the environment makes it hard to meet the assumptions, and it is difficult for a pre-set data model to adapt to a variety of environments. To solve the problem, this paper proposes an anomaly detection method on the foundation of machine learning and graph theory. First, the attributes of vertexes in the graph are set by the reconstruct errors. And then, robust background endmember dictionary and abundance matrix are received by structured sparse representation algorithm. Second, the Euler distances between pixels in lower-dimension are regarded as edge weights in the graph, after the analysis of the low dimensional manifold structure among the hyperspectral data, which is in virtue of manifold learning method. Finally, anomaly pixels are picked up by both vertex attributes and edge weights. The proposed method has higher probability of detection and lower probability of false alarm, which is verified by experiments on real images. © 2017 SPIE.
  Accession Number: 20180404671055
• Record 377 of
  
  Title:Small target detection in infrared image using convolutional neural networks
  
  Author(s):Wang, Wanting(1); Qin, Hanlin(1); Cheng, Wenxiong(1); Wang, Chunmei(1); Leng, Hanbing(2); Zhou, Huixin(1)
  Source: Proceedings of SPIE - The International Society for Optical Engineering  Volume: 10462  Issue:   DOI: 10.1117/12.2285689  Published: 2017  
  Abstract:Infrared small target detection is an important research topic in the field of infrared image processing and has a major impact on applications in areas such as remote sensing, infrared imaging precise. Due to atmospheric scattering, refraction and the effect of the lens, the infrared detector to receive the target information very weak, it's difficult to detect the small target in complex background. In this paper, a novel small target detection method in a single infrared image is proposed based on deep convolutional neural network that is mainly using to extract the features of target, through the method can obtain more discriminative features of infrared image. Firstly, the off-line training of convolution kernel parameters using open data sets and simulated data sets, the result of preliminary training gives an initial convolution kernel, this step can reduce the time required for parameter training. Secondly, the input infrared image is preliminarily processed by the trained parameters to obtain the primary features of the infrared image, through the processing of the convolution kernel, a large number of feature information in different scales of the input image are obtained. Finally, selecting and merging the features, design the efficient characteristic information selection strategy, then fine-Tune the convolution parameters with the result information, by merging the feature graph can realize the output of the result target image. The experimental results demonstrated that compared with existing classical methods, the proposed method could greatly improve the quality of the results, more importantly, our method can directly achieve the end-To-end mapping between the input images and target detection results. © 2017 SPIE.
  Accession Number: 20180404671010
• Record 378 of
  
  Title:Cost-optimized microblog distribution over geo-distributed data centers: Insights from cross-media analysis
  
  Author(s):Hu, Han(1); Wen, Yonggang(1); Chua, Tat-Seng(2); Li, Xuelong(3)
  Source: ACM Transactions on Intelligent Systems and Technology  Volume: 8  Issue: 3  DOI: 10.1145/3014431  Published: April 2017  
  Abstract:The unprecedent growth of microblog services poses significant challenges on network traffic and service latency to the underlay infrastructure (i.e., geo-distributed data centers). Furthermore, the dynamic evolution in microblog status generates a huge workload on data consistence maintenance. In this article, motivated by insights of cross-media analysis-based propagation patterns, we propose a novel cache strategy for microblog service systems to reduce the inter-data center traffic and consistence maintenance cost, while achieving low service latency. Specifically, we first present a microblog classification method, which utilizes the external knowledge from correlated domains, to categorize microblogs. Then we conduct a large-scale measurement on a representative online social network system to study the category-based propagation diversity on region and time scales. These insights illustrate social common habits on creating and consuming microblogs and further motivate our architecture design. Finally, we formulate the content cache problem as a constrained optimization problem. By jointly using the Lyapunov optimization framework and simplex gradient method, we find the optimal online control strategy. Extensive trace-driven experiments further demonstrate that our algorithm reduces the system cost by 24.5% against traditional approaches with the same service latency. © 2017 ACM.
  Accession Number: 20171703612605
• Record 379 of
  
  Title:N-vector inertial navigation mechanization algorithm for transpolar aircraft
  
  Author(s):Zhang, Guang-Dong(1); Yan, Gong-Min(2); Weng, Jun(2); Yang, Hong-Tao(1)
  Source: Zhongguo Guanxing Jishu Xuebao/Journal of Chinese Inertial Technology  Volume: 25  Issue: 5  DOI: 10.13695/j.cnki.12-1222/o3.2017.05.009  Published: October 1, 2017  
  Abstract:The classical mechanization working could not confirm its position and heading in the circumpolar latitude area. For overcoming this problem, the normal vector inertial navigation basing on earth-fixed frame is presented. This approach uses a normal vector instead of latitude/longitude to finish updating of position. It could achieve navigation requirement world-wide. The n-vector mechanization error equations are derived, which can be used in the design of integrated navigation systems. The simulation could test and verify the error characteristics of n-vector mechanization. The n-vector mechanization offers the solution to transpolar aircraft. The reason of the navigation error saltation near the pole area is explained. © 2017, Editorial Department of Journal of Chinese Inertial Technology. All right reserved.
  Accession Number: 20175004524946
• Record 380 of
  
  Title:A modified topological derivative based background suppression for infrared dim small target detection
  
  Author(s):Cheng, Wenxiong(1); Qin, Hanlin(1); Wang, Wanting(1); Wang, Chunmei(1); Leng, Hanbing(2); Zhou, Huixin(1)
  Source: Proceedings of SPIE - The International Society for Optical Engineering  Volume: 10462  Issue:   DOI: 10.1117/12.2285726  Published: 2017  
  Abstract:In the processing of infrared small target image which has low signal-To-noise ratio and complex background, the target detection and recognition are very hard. So, how to suppress infrared complex background in low signal-To-clutter addition becomes the key problem in the detection of infrared small target image. The topological derivative can quantify the sensitivity of a problem when the domain under consideration is perturbed by changing its topology. Considering the idea of topology optimization, a modified topological derivative based background suppression method for infrared dim small target detection was proposed. An appropriate functional and variational problem is related to the cost function. Thus, the corresponding topological derivative can be used as an indicator function leads to the processed image through a minimization process. Firstly, introduce perturbations to each pixel of the infrared image. Secondly, calculate the corresponding topological derivative. These pixels also have the least cost function. Finally, using the modified optimal diffusion coefficient to diffuse the pixels where the topological derivative is negative to make its background smooth and achieve the purpose of removing the background clutter while enhancing the small target. Compared with other several experiment results of existing background suppressing methods in indexes, the method the paper proposed has innovative ideas and gets well effects of background suppressing and are practical methods. All of above have the important research value for the related work in future. © 2017 SPIE.
  Accession Number: 20180404671016
• Record 381 of
  
  Title:Synthesis and spectroscopy of high concentration dysprosium doped GeS2[sbnd]Ga2S3[sbnd]CdI2chalcohalide glasses and fiber fabrication
  
  Author(s):Wang, Zixuan(1); Guo, Haitao(2); Xiao, Xusheng(2); Xu, Yantao(2); Cui, Xiaoxia(2); Lu, Min(2); Peng, Bo(2); Yang, Anping(3); Yang, Zhiyong(3); Gu, Shaoxuan(1)
  Source: Journal of Alloys and Compounds  Volume: 692  Issue:   DOI: 10.1016/j.jallcom.2016.09.085  Published: 2017  
  Abstract:0.2%–3% weight of Dy3+ions doped 64GeS2·16Ga2S3·20CdI2glasses were synthesized, and their spectroscopic properties were investigated. It was shown that the host glass could dissolve as much as 3% Dy3+ions without deteriorating the glass transparency. The mid-infrared (MIR) emissions of the glasses did not present remarkable concentration quenching when the Dy3+ions concentration was less than 0.6%. It was also shown that the MIR emission properties could be significantly improved by reducing S[sbnd]H/O[sbnd]H impurities in the glasses. The spectral analyses indicated that the 2.9 and 4.3 μm emissions of Dy3+ions in the glass showed relatively large stimulated emission cross sections. The glass doped with as high as 0.4% Dy3+ions was successfully drawn into fibers, indicating good potential of the doped glass for MIR lasers. © 2016 Elsevier B.V.
  Accession Number: 20164102887380
• Record 382 of
  
  Title:Athermalization of infrared dual field optical system based on wavefront coding
  
  Author(s):Kai, Jiang(1); Bo, Jiang(1); Kai, Liu(1); Peipei, Yan(1); Jing, Duan(1); Qiusha, Shan(1)
  Source: Proceedings of SPIE - The International Society for Optical Engineering  Volume: 10256  Issue:   DOI: 10.1117/12.2257873  Published: 2017  
  Abstract:Wavefront coding is a technology which combination of the optical design and digital image processing. By inserting a phase mask closed to the pupil plane of the optical system, the wavefront of the system is re-modulated. And the depth of focus is extended consequently. In reality the idea is same as the athermalization theory of infrared optical system. In this paper, an uncooled infrared dual field optical system with effective focal as 38mm/19mm, F number as 1.2 of both focal length, operating wavelength varying from 8μm to 12μm was designed. A cubic phase mask was used at the pupil plane to re-modulate the wavefront. Then the performance of the infrared system was simulated with CODEV as the environment temperature varying from -40°C to 60°C. MTF curve of the optical system with phase mask are compared with the outcome before using phase mask. The result show that wavefront coding technology can make the system not sensitive to thermal defocus, and then realize the athermal design of the infrared optical system. © 2017 SPIE.
  Accession Number: 20171703607568
• Record 383 of
  
  Title:Robust Web Image Annotation via Exploring Multi-Facet and Structural Knowledge
  
  Author(s):Hu, Mengqiu(1); Yang, Yang(1); Shen, Fumin(1); Zhang, Luming(2); Shen, Heng Tao(1); Li, Xuelong(3)
  Source: IEEE Transactions on Image Processing  Volume: 26  Issue: 10  DOI: 10.1109/TIP.2017.2717185  Published: October 2017  
  Abstract:Driven by the rapid development of Internet and digital technologies, we have witnessed the explosive growth of Web images in recent years. Seeing that labels can reflect the semantic contents of the images, automatic image annotation, which can further facilitate the procedure of image semantic indexing, retrieval, and other image management tasks, has become one of the most crucial research directions in multimedia. Most of the existing annotation methods, heavily rely on well-labeled training data (expensive to collect) and/or single view of visual features (insufficient representative power). In this paper, inspired by the promising advance of feature engineering (e.g., CNN feature and scale-invariant feature transform feature) and inexhaustible image data (associated with noisy and incomplete labels) on the Web, we propose an effective and robust scheme, termed robust multi-view semi-supervised learning (RMSL), for facilitating image annotation task. Specifically, we exploit both labeled images and unlabeled images to uncover the intrinsic data structural information. Meanwhile, to comprehensively describe an individual datum, we take advantage of the correlated and complemental information derived from multiple facets of image data (i.e., multiple views or features). We devise a robust pairwise constraint on outcomes of different views to achieve annotation consistency. Furthermore, we integrate a robust classifier learning component via 2,p loss, which can provide effective noise identification power during the learning process. Finally, we devise an efficient iterative algorithm to solve the optimization problem in RMSL. We conduct comprehensive experiments on three different data sets, and the results illustrate that our proposed approach is promising for automatic image annotation. © 2017 IEEE.
  Accession Number: 20172703894842
• Record 384 of
  
  Title:Optimized design of fast single image dehazing algorithm
  
  Author(s):Yang, Lei(1); Bian, He(1); Feng, Jia(1); Zhao, Lisha(2); Wang, Hua(1); Liu, Qing(1); Wang, Hao(1); Wang, Huawei(1); Liao, Jiawen(1)
  Source: 2016 13th International Computer Conference on Wavelet Active Media Technology and Information Processing, ICCWAMTIP 2017  Volume: 2018-February  Issue:   DOI: 10.1109/ICCWAMTIP.2017.8301472  Published: July 2, 2017  
  Abstract:Imaging in the atmosphere presents the phenomenons of low contrast, low saturation and hue offset due to atmospheric particles such as haze and fog. In this paper, an optimized design method is proposed to remove haze from a single image. Based on the atmospheric scattering model, dark channel prior is used to estimate the value of global atmospheric light by an interval. Meanwhile, the initial estimation of medium transmission is obtained. And the white balance is performed to simplify the atmospheric scattering model. Then, to deal with the invalid case of the dark channel, we exploit a scheme to identify bright area based on dual threshold and develop a way to correct transmission rate, which enables the dark channel prior to be more applicable. Finally, enhanced processing is introduced by adopting nonlinear contrast stretching, which improves the visual effect of dehazing images. The experimental results show that the proposed method can achieve a faster processing speed, effectively improve the visibility and contrast of the restored image, and obtain good color effect. © 2017 IEEE.
  Accession Number: 20183105636047