2019
2019
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Record 1 of
Title:Design and Analysis of Radiometric Calibration Mission in-orbit for Environment and Disasters Monitoring Satellite
Author(s):Zhu, Yang(1,2); Zhu, Jun(2); Bai, Zhaoguang(2); Dong, Jun(2); Wu, Bin(2); Huang, Min(2); Yin, Huan(2); Cao, Qipeng(2); Hong, Jin(3); Sun, Dexin(4); Liu, Xuebin(5); Jin, Lifeng(6)Source: International Geoscience and Remote Sensing Symposium (IGARSS) Volume: Issue: DOI: 10.1109/IGARSS.2019.8899841 Published: July 2019Abstract:With the rapid improvement of optical payload radiometric calibration accuracy, it is necessary to carry out in-orbit radiometric calibration to improve the calibration accuracy and image quality. The design and analysis of in-orbit radiometric calibration with moon, sun and side-slither is presented. The side-slither radiometric calibration mission based on along track scanning is proposed to obtain 60 angles polarization Stokes parameters with the calibration target of deep convective cloud. The satellite attitude stability for in-orbit radiometric calibration is analyzed and meets the requirements of optical image quality. ? 2019 IEEE.Accession Number: 20200208025621 -
Record 2 of
Title:Incoherent space beam combining of fiber-transmitted semiconductor lasers for oil well laser perforation
Author(s):Bai, Yang(1,2); Lei, Guangzhi(3); Chen, Haowei(1,2); Feng, Xiaoqiang(1,2); Li, Diao(1,2); Bai, Jintao(1,2)Source: IEEE Access Volume: 7 Issue: DOI: 10.1109/ACCESS.2019.2919784 Published: 2019Abstract:This paper demonstrates a 19 × 1 incoherent space beam combiner tailored for oil well laser perforation, which is used for an incoherent laser beam combining of 19 fiber-transmitted semiconductor lasers around a wavelength of 972 nm. The parameters of the combiner and its used optical lens are optimized, which is attributed to the theoretical analysis of the variation law between the radii, the spacing of collimating laser beams, and the spot overlap rate of the combined laser beam, respectively, and the simulation of the cross-sectional energy distribution of the beam combiner. A beam combining the power of 10.159 kW is achieved with an average beam combining efficiency of higher than 98.2%, a beam combining length of 300 mm, and a focal spot diameter of 21 mm. A laser perforation experiment is performed for a granite sample using a 10-kW space incoherent beam laser, and a perforation depth of 960 mm is obtained. This paper underscores the design philosophy of the incoherent space beam combiner with ultra-high laser power, a long beam combining length, a simple structure, and a high downhole transmission safety, and builds the foundation for applications of the incoherent space beam combined laser in the oil well perforation. ? 2013 IEEE.Accession Number: 20200308053929 -
Record 3 of
Title:Hierarchical recurrent neural network for video summarization
Author(s):Zhao, Bin(1); Li, Xuelong(2); Lu, Xiaoqiang(2)Source: arXiv Volume: Issue: DOI: null Published: April 27, 2019Abstract:Exploiting the temporal dependency among video frames or subshots is very important for the task of video summarization. Practically, RNN is good at temporal dependency modeling, and has achieved overwhelming performance in many video-based tasks, such as video captioning and classiffication. However, RNN is not capable enough to handle the video summarization task, since traditional RNNs, including LSTM, can only deal with short videos, while the videos in the summarization task are usually in longer duration. To address this problem, we propose a hierarchical recurrent neural network for video summarization, called H-RNN in this paper. Speciffically, it has two layers, where the ffirst layer is utilized to encode short video subshots cut from the original video, and the ffinal hidden state of each subshot is input to the second layer for calculating its conffidence to be a key subshot. Compared to traditional RNNs, H-RNN is more suitable to video summarization, since it can exploit long temporal dependency among frames, meanwhile, the computation operations are signifficantly lessened. The results on two popular datasets, including the Combined dataset and VTW dataset, have demonstrated that the proposed H-RNN outperforms the state-of-the-arts. Copyright ? 2019, The Authors. All rights reserved.Accession Number: 20200532850 -
Record 4 of
Title:Analysis on the radiation effects of a charge-coupled device in a space debris detection satellite in orbit
Author(s):Li, Yudong(1); Wen, Lin(1); Huang, Jianyu(2); Wen, Yan(3); Zhang, Keke(4); Guo, Qi(1)Source: Yaogan Xuebao/Journal of Remote Sensing Volume: 23 Issue: 1 DOI: 10.11834/jrs.20197144 Published: January 25, 2019Abstract:High-performance Charge-Coupled Devices (CCDs) are the preeminent detectors for space-based photoelectric detection. However, the vulnerability of CCDs to radiation damage in the space radiation environment is a serious threat to space imaging applications in terms of earth-observing spectral measurement and space debris detection. Observing the in-orbit radiation effects of CCDs used in a space imaging system is crucial. This kind of work can provide essential data for the in-orbit maintenance and future design of a space mission. Through calculation and analysis using plenty of in-orbit images generated by a space debris detection experiment satellite, several kinds of imaging abnormalities caused by the space radiation environment of the satellite are observed. The radiation damage on the CCD imager used in the satellite's visible camera is assessed. First, the abnormal phenomenon of imaging functions is described. Second, transient effects and hot pixels induced by protons in the space environment are analyzed. In addition, the total ionizing dose effects and displacement damage of the CCD imager are estimated to help predict the long-term in-orbit performance of the device. The transient effects mainly result from the instantaneous ionization in pixel structures induced by protons from the South Atlantic Anomaly (SAA). When the satellite traversed the SAA, the number of transient effects is changed in proportion to the proton flux in this position in the SAA. The number of transient effects for one traversing agrees with the Gaussian distribution. All the hot pixels present a high dark current several times larger than that of most normal pixels. The number of hot pixels increase with the time in-orbit of the satellite. The increase is almost linear with the run time or the times passed through the SAA. The hot pixels are mainly attributed to the single particle displacement damage induced by energetic protons in the SAA. No observable correlation is noted between hot pixels and transient effects. The principal influence on the CCD imager is the increase of hot pixels with the time in-orbit. Even in the early stage after the launch of the satellite, the influence of CCD's hot pixels may be significant, an outcome that is clearly different from the accumulated radiation damage (total ionizing dose effects and accumulated displacement damage) on CCDs. The results of the above work suggest that critical information is obtained for operational risk assessment and in-orbit management of the satellite. In addition, the methodology is formed for in-orbit radiation degradation prediction on image sensor and optical payload. The method may be useful for radiation hardness on a space-based debris detection satellite, which is situated in either low or high earth orbit. The mechanisms of hot pixels generated by proton bombardment still require further study. ? 2019, Science Press. All right reserved.Accession Number: 20191106643608 -
Record 5 of
Title:Optical Design of a Compound Eye Camera with a Large-field of View for Unmanned Aerial Vehicles
Author(s):Yu, Xiao-Dan(1,2); Zhang, Yuan-Jie(1,2); Wang, Yuan-Yuan(1,3); Xu, Huang-Rong(1,2); Yu, Wei-Xing(1,2)Source: Guangzi Xuebao/Acta Photonica Sinica Volume: 48 Issue: 7 DOI: 10.3788/gzxb20194807.0722003 Published: July 1, 2019Abstract:A large field of view Unmanned Aerial Vehicle (UAV) camera imaging system, named curved compound eye camera for the small UAV, was designed. The system consists of three subsystems, a cured microlens arrays, an optical transformation subsystem, and a data processing unit with image sensors. The designed compound camera has a focal length of 4 mm, a F number of 4, and a field of view is 106°, which makes it can resolve the ground target with a feature size of 0.5 m at an altitude of 500 m. In the design, lenslets with a doublet form were used in curved compound eye to eliminate the optical abberations. Since there is an overlap in field of view for neighboring lenslets, lenslets as much as of 7 can view the same target at the same time from different view angles, which allows the object location and speed measurement. The simulation results show that the image quality of the entire compound eye camera system meets the requirements with an acceptable tolerance, and the maximum optical distortion can be controlled under 1.2%. ? 2019, Science Press. All right reserved.Accession Number: 20193407327516 -
Record 6 of
Title:Low-rank 2-D neighborhood preserving projection for enhanced robust image representation
Author(s):Lu, Yuwu(1); Lai, Zhihui(1,2); Li, Xuelong(3,4); Wong, Wai Keung(2); Yuan, Chun(5); Zhang, David(6)Source: IEEE Transactions on Cybernetics Volume: 49 Issue: 5 DOI: 10.1109/TCYB.2018.2815559 Published: May 2019Abstract:2-D neighborhood preserving projection (2DNPP) uses 2-D images as feature input instead of 1-D vectors used by neighborhood preserving projection (NPP). 2DNPP requires less computation time than NPP. However, both NPP and 2DNPP use the L2 norm as a metric, which is sensitive to noise in data. In this paper, we proposed a novel NPP method called low-rank 2DNPP (LR-2DNPP). This method divided the input data into a component part that encoded low-rank features, and an error part that ensured the noise was sparse. Then, a nearest neighbor graph was learned from the clean data using the same procedure as 2DNPP. To ensure that the features learned by LR-2DNPP were optimal for classification, we combined the structurally incoherent learning and low-rank learning with NPP to form a unified model called discriminative LR-2DNPP (DLR-2DNPP). By encoding the structural incoherence of the learned clean data, DLR-2DNPP could enhance the discriminative ability for feature extraction. Theoretical analyses on the convergence and computational complexity of LR-2DNPP and DLR-2DNPP were presented in details. We used seven public image databases to verify the performance of the proposed methods. The experimental results showed the effectiveness of our methods for robust image representation. ? 2018 IEEE.Accession Number: 20181504989847 -
Record 7 of
Title:Co-occurrence matching of local binary patterns for improving visual adaption and its application to smoke recognition
Author(s):Yuan, Feiniu(1,2); Shi, Jinting(3); Xia, Xue(2); Huang, Qinghua(4); Li, Xuelong(5)Source: IET Computer Vision Volume: 13 Issue: 2 DOI: 10.1049/iet-cvi.2018.5164 Published: March 1, 2019Abstract:It is challenging to recognize smoke from visual scenes due to large variations of smoke colors, textures and shapes. To improve robustness, we propose a novel feature extraction method based on similarity and dissimilarity matching measures of Local Binary Patterns (LBP). Given two bit-sequences of an LBP code pair, the similarity and dissimilarity matching measures are defined as the ratios of the 1-1 bitwise matching number to the 0-0 bitwise matching number and the 1-0 number to the 0-1 number, respectively. To capture local code variations, we calculate the measures between LBP codes of a center pixel and its neighbors. Then we compare each measure with its global mean to propose Similarity Matching based Local Binary Patterns (SMLBP) and Dissimilarity Matching based Local Binary Patterns (DMLBP). Since SMLBP and DMLBP extract spatial variations of the 1st order LBP codes, they actually represent the 2nd order variations of pixel values. Furthermore, we adopt different mapping modes and multi-scale neighborhoods to obtain rotation and scale invariances. Finally, we concatenate the histograms of LBP, SMLBP and DMLBP to generate a feature vector containing 1st and 2nd order information. Experiments show that our method obviously outperforms existing methods. ? The Institution of Engineering and Technology 2018.Accession Number: 20190906559203 -
Record 8 of
Title:Improving the image reconstruction quality of compressed ultrafast photography via an augmented Lagrangian algorithm
Author(s):Yang, Chengshuai(1); Qi, Dalong(1); Cao, Fengyan(1); He, Yilin(1); Wang, Xing(2); Wen, Wenlong(2); Tian, Jinshou(2); Jia, Tianqing(1); Sun, Zhenrong(1); Zhang, Shian(1,3)Source: Journal of Optics (United Kingdom) Volume: 21 Issue: 3 DOI: 10.1088/2040-8986/ab00d9 Published: February 14, 2019Abstract:Compressed ultrafast photography (CUP) has been shown to be a powerful tool to measure ultrafast dynamic scenes. In previous studies, CUP used a two-step iterative shrinkage/thresholding (TwIST) algorithm to reconstruct three-dimensional image information. However, the image reconstruction quality greatly depended on the selection of the penalty parameter, which caused the reconstructed images to be unable to be correctly determined if the ultrafast dynamic scenes were unknown in advance. Here, we develop an augmented Lagrangian (AL) algorithm for the image reconstruction of CUP to overcome the limitation of the TwIST algorithm. Our numerical simulations and experimental results show that, compared to the TwIST algorithm, the AL algorithm is less dependent on the selection of the penalty parameter, and can obtain higher image reconstruction quality. This study solves the problem of the image reconstruction instability, which may further promote the practical applications of CUP. ? 2019 IOP Publishing Ltd.Accession Number: 20191506771875 -
Record 9 of
Title:A Bilinear Ranking SVM for Knowledge Based Relation Prediction and Classification
Author(s):Yu, Shengkang(1,2); Li, Xi(3); Zhao, Xueyi(1); Zhang, Zhongfei(1); Wu, Fei(3); Wang, Jingdong(4); Zhuang, Yueting(3); Li, Xuelong(5)Source: IEEE Transactions on Big Data Volume: 5 Issue: 4 DOI: 10.1109/TBDATA.2018.2843766 Published: December 1, 2019Abstract:As an important and challenging problem, knowledge representation and inference are typically carried out in a knowledge embedding framework over a multi-relational knowledge graph, and thus have a wide range of applications such as semantic retrieval and question answering. In this paper, we propose a bilinear learning framework which performs cross-entity knowledge relation analysis in the continuous vector space (derived from knowledge embedding). In the framework, we effectively model the intrinsic correlations among different types of knowledge relations within a max-margin multi-relational ranking scheme, which jointly optimizes the tasks of entity embedding and cross-entity relation prediction in terms of multi-relational structures of the knowledge graph. Specifically, we devise a bilinear scoring function that aims to evaluate the confidence degree of semantic relation prediction for entity pairs through a multi-relational learning-to-rank pipeline. In essence, the pipeline formulates the problem of relation prediction for entity pairs as that of learning relation-specific ranking functions by max-margin optimization. Experimental results demonstrate the effectiveness of the proposed framework on two common benchmark datasets. ? 2015 IEEE.Accession Number: 20182505336594 -
Record 10 of
Title:Antimonide-based visible to short wavelength infrared bispectral photodetector
Author(s):Guo, Chunyan(1,2,4,6); Ding, Ying(3,4,5); Wasige, Edward(4); Jia, Qingxuan(5,6); Wang, Guowei(5,6); Xu, Yingqiang(5,6); Niu, Zhichuan(5,6); Wang, Tao(1); Tian, Jinshou(1,7); Wu, Zhaoxin(2,7)Source: Proceedings of SPIE - The International Society for Optical Engineering Volume: 11031 Issue: DOI: 10.1117/12.2520738 Published: 2019Abstract:We report cylinder photon traps, prism photon traps, and SiO2/Ta2O5 antireflection films added to the active areas of short wavelength infrared detectors. The total device thickness was estimated ～3.3μm and with the p-i-n structure based on antimonide. The simulation results show that the photon traps increase the absorption of the invisible spectrum distinctly. Also, the optical measurements reveal that maximal responsivity of the detector with PTs array is 0.094A/W in the visible range and 0.64A/W in the short wavelength infrared spectrum. The responsivity in the wavelength of short-wave infrared can be increased apparently as well. Thus, the photon traps array may a potential method for antimonide-based visible to short wavelength infrared bispectral photodetector. ? 2019 SPIE. Downloading of the abstract is permitted for personal use only.Accession Number: 20193207270970 -
Record 11 of
Title:Broadband photonic RF channelization based on an integrated optical micro-comb source
Author(s):Jia, Linnan(1); Xu, Xingyuan(1); Wu, Jiayang(1); Tan, Mengxi(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: Proceedings of SPIE - The International Society for Optical Engineering Volume: 11200 Issue: DOI: 10.1117/12.2540360 Published: 2019Abstract:We demonstrate broadband radio frequency (RF) channelization based on a CMOS-compatible integrated optical micro-comb source, which provides a large number of wavelength channels as well as an RF operation bandwidth of ～90 GHz. We experimentally verify the RF channelization performance from ～1.7 GHz to ～19 GHz with a high spectral slice resolution of ～1.04 GHz. ? COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.Accession Number: 20200808205245 -
Record 12 of
Title:Automated fine motor evaluation for developmental coordination disorder
Author(s):Li, Ruimin(1,2,3); Fu, Hong(3); Zheng, Yang(1,2,3); Lo, Wai-Lun(3); Yu, Jane J.(4); Sit, Cindy H. P.(4); Chi, Zheru(5); Song, Zongxi(6); Wen, Desheng(6)Source: IEEE Transactions on Neural Systems and Rehabilitation Engineering Volume: 27 Issue: 5 DOI: 10.1109/TNSRE.2019.2911303 Published: May 2019Abstract:Developmental coordination disorder (DCD) is a type of motor learning difficulty that affects five to six percent of school-Aged children, which may have a negative impact on the life of the sufferers. Timely and objective diagnosis of DCD are important for the success of the intervention. The present evaluation methods of DCD rely heavily on the observational analysis of occupational therapists and physiotherapists, who score the performance when children conduct some designed tasks. However, these methods are expensive, subjective, and are not easy to expand to a larger population. A fine motor evaluation system (FMES) is proposed with two views of cameras to record children's performance, when they carry out three fine motor tasks. Automated algorithms are developed to perform automated scoring of fine motor skill. The automated algorithms include task localization and individual task evaluation. The purpose of task localization is to detect each task and extract segments belonging to each task from the original video that includes multiple segments of different tasks. A convolutional neural network with temporal filtering is used to do frame-wise classification, and a boundary localization algorithm is proposed to localize each task segment. For individual task evaluation, the extracted video segments of task 1 and task 2 are evaluated based on the proposed feature extraction and time positioning algorithm, and the paper drawings of task 3 are evaluated based on image processing. The proposed methods are validated on a diverse population of children with or without DCD by comparing automated scoring with manual scoring from a professional evaluator. The experimental results suggest that the proposed methods can effectively achieve fine motor evaluation for DCD assessment. Besides, our system is a low-cost solution, and the evaluation methods developed are automated, objective, and can be suited for large population evaluation and analysis. ? 2001-2011 IEEE.Accession Number: 20192006930919