2020

• Record 25 of
  
  Title:Lasercom optical-terminal performance testing platform
  
  Author(s):Li, Jing(1); Xue, Xun(1); Wang, Zhengfeng(1); Liu, Kai(1); Zhou, Yan(1); Zhao, Jianke(1)
  Source: Optik  Volume: 224  Issue:   DOI: 10.1016/j.ijleo.2020.165521  Published: December 2020  
  Abstract:The lasercom optical-terminal performance testing platform (LCOT-PTP) is a precision optical system providing experimental testing of important characteristic parameters including transmitting power, beam divergence angle, far-field spot energy distribution and coaxialities of different branches in a lasercom optical terminal (LCOT). The LCOT-PTP consisting of a telescope, beam splitters, a receiving branch, a transmitting branch and a tracking test branch is developed. Due to the testing process requirements in coarse tracking, fine tracking and the assembly integration, the working wavelengths of 808nm, 1550nm and 632.8nm are adopted in testing-system design. By using the under-test LCOT parameters and Gaussian beam transmitting theory, the optical-system design is completed. Based on the established LCOT-PTP, the key performance testing work is accomplished. © 2020 Elsevier GmbH
  Accession Number: 20204009265882
• Record 26 of
  
  Title:Mathematical Derivation and Parameter Analysis of Phase-sensitive Detection Principle
  
  Author(s):Wang, Haisen(1,2); Wang, Rui(1,2); Qiao, Yongming(1); Lv, Tao(1,2); Yang, Lulu(1,2)
  Source: Proceedings - 2020 12th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2020  Volume: 2  Issue:   DOI: 10.1109/IHMSC49165.2020.10081  Published: August 2020  
  Abstract:Phase-sensitive detection is an effective method for high-precision detection of weak signals, but there is no detailed derivation and description of this principle in the previous literatures. This article based on the basic principle of phase-sensitive detection gives two different derivation methods of analog and digital phase-sensitive detection principles. Then the Matlab is used to verify the digital phase-sensitive detection principle and analyze the parameters. Finally, this article gives a reasonable range of parameter selection for phase-sensitive detection and guides the reader to make a good parameter selection when using phase-sensitive detection. © 2020 IEEE.
  Accession Number: 20204409407299
• Record 27 of
  
  Title:Hemoglobin detection based on excessively tilted fiber grating by non-covalent bonding
  
  Author(s):Sun, Yuezhen(1); Lu, Tean(1); Wang, Hushan(3); Sun, Qizhen(1,2); Yan, Zhijun(1,2); Liu, Deming(1,2)
  Source: Optics InfoBase Conference Papers  Volume:   Issue:   DOI: null  Published: October 24, 2020  
  Abstract:We have demonstrated a novel hemoglobin sensor based on hydroxide bond functionalized excessively tilted fiber grating. Due to non-covalent bonding between hydroxide bond and hemoglobin, such sensor could achieve hemoglobin detection with sensitivity around 1.93nm/(mg/ml). © OSA 2020, © 2020 The Author(s)
  Accession Number: 20211110067785
• Record 28 of
  
  Title:Channel-Grouping Based Patch Swap for Arbitrary Style Transfer
  
  Author(s):Zhu, Yan(1); Niu, Yi(1); Li, Fu(1); Zou, Chunbo(2); Shi, Guangming(1)
  Source: Proceedings - International Conference on Image Processing, ICIP  Volume: 2020-October  Issue:   DOI: 10.1109/ICIP40778.2020.9190962  Published: October 2020  
  Abstract:The basic principle of the patch-matching based style transfer is to substitute the patches of the content image feature maps by the closest patches from the style image feature maps. Since the finite features harvested from one single aesthetic style image are inadequate to represent the rich textures of the content natural image, existing techniques treat the full-channel style feature patches as simple signal tensors and create new style feature patches via signal-level fusion. In this paper, we propose a channel-grouping based patch swap technique to group the style feature maps into surface and texture channels, and the new features are created by the combination of these two groups, which can be regarded as a semantic-level fusion of the raw style features. Experimental results demonstrate that the proposed method outperforms the existing techniques in providing more style-consistent textures while keeping the content fidelity. © 2020 IEEE.
  Accession Number: 20210109724787
• Record 29 of
  
  Title:Gated and Axis-Concentrated Localization Network for Remote Sensing Object Detection
  
  Author(s):Lu, Xiaoqiang(1); Zhang, Yuanlin(1,2); Yuan, Yuan(3); Feng, Yachuang(1)
  Source: IEEE Transactions on Geoscience and Remote Sensing  Volume: 58  Issue: 1  DOI: 10.1109/TGRS.2019.2935177  Published: January 2020  
  Abstract:In the multicategory object detection task of high-resolution remote sensing images, small objects are always difficult to detect. This happens because the influence of location deviation on small object detection is greater than on large object detection. The reason is that, with the same intersection decrease between a predicted box and a true box, Intersection over Union (IoU) of small objects drops more than those of large objects. In order to address this challenge, we propose a new localization model to improve the location accuracy of small objects. This model is composed of two parts. First, a global feature gating process is proposed to implement a channel attention mechanism on local feature learning. This process takes full advantages of global features' abundant semantics and local features' spatial details. In this case, more effective information is selected for small object detection. Second, an axis-concentrated prediction (ACP) process is adopted to project convolutional feature maps into different spatial directions, so as to avoid interference between coordinate axes and improve the location accuracy. Then, coordinate prediction is implemented with a regression layer using the learned object representation. In our experiments, we explore the relationship between the detection accuracy and the object scale, and the results show that the performance improvements of small objects are distinct using our method. Compared with the classical deep learning detection models, the proposed gated axis-concentrated localization network (GACL Net) has the characteristic of focusing on small objects. © 2019 IEEE.
  Accession Number: 20200308053970
• Record 30 of
  
  Title:A new phase retrieval method using sequential phase modulations
  
  Author(s):Chen, Xiaoyi(1,2); Duan, Yaxuan(1); Li, Hongguang(1); Wang, Pu(1); Li, Ming(1); Da, Zhengshang(1)
  Source: Applied Physics B: Lasers and Optics  Volume: 126  Issue: 5  DOI: 10.1007/s00340-020-7417-3  Published: May 1, 2020  
  Abstract:In this paper, a new phase retrieval method using sequential phase modulations is proposed. Behind the unknown object, adding sequential phase modulations will change the diffraction intensities received by sensor. Through increasing the number of diffraction intensities patterns, the difficulty of retrieving the unknown object is decreased. To better select these modulation phases, the complexity parameter is defined to evaluate the complexity of unknown object. When the complexity parameter of unknown object is larger, it contains more spectrum information on different frequency bands and will be harder to retrieve. The complexity of unknown object should be contained between the maximum and minimum complexities of modulation phases. In this way, the information of each frequency band on the unknown object can be effectively retrieved. Meanwhile, the distribution of modulation phases should be continuous to avoid introducing high frequency noise. In addition, there is no limit on what kind of modulation phase distribution to choose. The effectiveness and fast convergence of this new method has been proved. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.
  Accession Number: 20201508404205
• Record 31 of
  
  Title:Physical and Mechanical Characteristics of Lunar Soil at the Chang'E-4 Landing Site
  
  Author(s):Tang, Zhencheng(1,2); Liu, Jianjun(1,2); Wang, Xing(1,2); Ren, Xin(1); Chen, Wangli(1); Yan, Wei(1); Zhang, Xiaoxia(1); Tan, Xu(1); Zeng, Xingguo(1); Liu, Dawei(1); Zhang, Hongbo(1,2); Wen, Weibin(1); Zuo, Wei(1,2); Su, Yan(1,2); Yang, Jianfeng(3); Li, Chunlai(1,2)
  Source: Geophysical Research Letters  Volume: 47  Issue: 22  DOI: 10.1029/2020GL089499  Published: November 28, 2020  
  Abstract:Chang'E-4, with the Yutu-2 rover, is the first lunar probe to successfully land and conduct a tour on the far side of the Moon from early 2019. We analyze the physical and mechanical characteristics of lunar soil through the in situ terrain data collected by the panoramic camera onboard the Yutu-2 rover. With the slip ratio and wheel sinkage obtained by the derived Digital Orthophoto Map (DOM) and Digital Elevation Model (DEM), the mechanical parameters of lunar soil are derived from the slip-sinkage model. These mechanical parameters and wheel size of the rover are used to obtain the pressure-sinkage curves, which can estimate the lunar soil strength. The experimental results indicate that the soil strength at the Chang'E-4 landing site is much higher than that at the Chang'E-3 landing site. The discrepancies in lunar soil strength between the two landing sites may be related to the local surface topography and degree of space weathering. ©2020. American Geophysical Union. All Rights Reserved.
  Accession Number: 20204809541245
• Record 32 of
  
  Title:Investigating the effect of source contamination on eXTP/SFA
  
  Author(s):Zhang, Juan(1); Li, Gang(1); Ge, Mingyu(1); Kirsch, Christian(2); Lorenz, Maximilian(2); Wilms, Joern(2); Qi, Liqiang(1); Sheng, Lizhi(3); Yang, Yi-Jung(1); Dauser, Thomas(2); Xu, Yupeng(1); Lu, Fangju(1); Yang, Yanji(1); Wang, Yusa(1); Chen, Yong(1)
  Source: Proceedings of SPIE - The International Society for Optical Engineering  Volume: 11444  Issue:   DOI: 10.1117/12.2561944  Published: 2020  
  Abstract:The Spectroscopy Focusing Array (SFA) onboard the enhanced X-ray Timing and Polarimetry (eXTP) observatory consists of 9 modules, each comprising a Wolter type I telescope with a field of view (FOV) around 16 arcminutes and a focal plane silicon drift detector (SDD) with 19 hexagonal pixels. Due to the large size of each individual SDD pixel (each pixel corresponds to an area of ∼ 3.6 arcminutes in diameter) and the limited pixel number, SFA can not obtain a real image of the observed region like many other X-ray imaging telescopes. Thus, contamination from nearby bright sources needs to be considered when we study the properties of the target source. We simulate such contaminations using the SIXTE simulator. In this paper we present the results by taking observations of the millisecond pulsar PSR J0437-4715 as an example, and discuss the cases for contamination on background or target source respectively. © 2020 SPIE
  Accession Number: 20210309778734
• Record 33 of
  
  Title:A Non-local Rank-Constraint Hyperspectral Images Denoising Method with 3-D Anisotropic Total Variation
  
  Author(s):Gong, Tao(1,2); Wen, Desheng(1); He, Tianbin(1)
  Source: Journal of Physics: Conference Series  Volume: 1438  Issue: 1  DOI: 10.1088/1742-6596/1438/1/012024  Published: January 11, 2020  
  Abstract:Hyperspectral Images (HSIs) are usually degraded by many kinds of noise called mixed noise, which greatly limits the subsequent applications of HSIs. Many researches have proved the patch-based low-rank methods and the total variation (TV) based approaches have a good effect on reducing noise in HSIs. Here, we propose a non-local patch based rank-constraint HSIs noise suppression methods with a global 3-D anisotropic total variation (NLRATV). Differing from previous patch-based methods which usually ignore spatial structural information, we add more structural constraints with the non-local similarity across patches for suppressing the structural noise that exists at the same location of many bands. Besides, we utilize the global 3-D anisotropic total variation to ensure its smoothness in spatial and spectral dimensionalities while reconstructing the image. The augmented Lagrange multiplier method is adopted to optimize the proposed algorithm. The real data experiments have proved the superiority of NLRATV in decreasing mixed and dense noise. © Published under licence by IOP Publishing Ltd.
  Accession Number: 20200708159015
• Record 34 of
  
  Title:Application of target tracking and abnormal target detection algorithm in power network security
  
  Author(s):Yang, Xianwei(1,2); Wang, Weifeng(1)
  Source: Proceedings of SPIE - The International Society for Optical Engineering  Volume: 11373  Issue:   DOI: 10.1117/12.2557202  Published: 2020  
  Abstract:Targets such as plastic bags can absorb a lot of high-energy lasers which fired from the laser in a long distance. By aligning the laser center with the optical center of the high definition camera, we can determine that the laser emission point is located at the center of video. We can adjust the angle and position of the camera to make the video center coincide with the target, and finally accurately clean up the target from a long distance. In the process of video, this paper uses the target tracking algorithm based on template and the abnormal target detection method based on inter-frame difference. After we lock the target to be cleaned in a frame, the system can automatically calculate the angle and distance if the target swings in the wind, and send the corresponding motion command to the rotating device which can drive the camera to move, finally realize the target tracking and cleaning. Abnormal target detection algorithm is used to monitor the designated area near the target while emitting high-energy laser. When abnormal target such as human is found to enter, protection mechanism is triggered in time to turn off laser which can prevent dangerous accidents. © 2019 SPIE.
  Accession Number: 20200908219748
• Record 35 of
  
  Title:Method for black ice detection on roads using tri-wavelength backscattering measurements
  
  Author(s):Ma, Xinxu(1,2); Ruan, Chi(1)
  Source: Applied Optics  Volume: 59  Issue: 24  DOI: 10.1364/AO.398772  Published: August 20, 2020  
  Abstract:This paper provides a method of detecting black ice on a road surface by multiwavelength noncontact optical technology. The laser sources, wavelengths of 1310, 1430, and 1550 nm, were irradiated on the road surface. Then, we define the ratio of the backscattering power under a certain condition to the backscattering power under dry conditions as the normalized reflectance. It is found that the normalized reflectance under dry, water, black ice, icy, and snowy conditions is different. Therefore, the normalized reflectance can be used to identify black ice on a road surface. © 2020 Optical Society of America
  Accession Number: 20203609121400
• Record 36 of
  
  Title:Unregistered Hyperspectral and Multispectral Image Fusion with Synchronous Nonnegative Matrix Factorization
  
  Author(s):Chen, Wenjing(1,2); Lu, Xiaoqiang(1)
  Source: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)  Volume: 12305 LNCS  Issue:   DOI: 10.1007/978-3-030-60633-6_50  Published: 2020  
  Abstract:Recently, many methods have been proposed to generate a high spatial resolution (HR) hyperspectral image (HSI) by fusing HSI and multispectral image (MSI). Most methods need a precondition that HSI and MSI are well registered. However, in practice, it is hard to acquire registered HSI and MSI. In this paper, a synchronous nonnegative matrix factorization (SNMF) is proposed to directly fuse unregistered HSI and MSI. The proposed SNMF does not require the registration operation by modeling the abundances of unregistered HSI and MSI independently. Moreover, to exploit both HSI and MSI in the endmember optimization of the desired HR HSI, the unregistered HSI and MSI fusion is formulated as a bound-constrained optimization problem. A synchronous projected gradient method is proposed to solve this bound-constrained optimization problem. Experiments on both simulated and real data demonstrate that the proposed SNMF outperforms the state-of-the-art methods. © 2020, Springer Nature Switzerland AG.
  Accession Number: 20204409410245