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Record 205 of
Title:Quantitative atmospheric rendering for real-time infrared scene simulation
Author(s):Wu, Xin(1); Zhang, Chi(1); Huang, Melin(1,2); Yang, Chen(3); Ding, Guopeng(1)
Source: Infrared Physics and Technology Volume: 114 Issue: DOI: 10.1016/j.infrared.2020.103610 Published: May 2021
Abstract:The radiation transfer of the Earth's atmosphere is a complex progress, which involves electromagnetic propagation, thermodynamics, and molecular spectroscopy. Atmospheric effects on an infrared scene were presented as transmission, absorption, and scattering. Atmospheric rendering thus aims to visually display these effects of the radiation through the Earth's atmosphere. In this paper, a quantitative atmospheric rendering method was proposed for real-time infrared scene simulation. By counting the selective absorption of water, carbon dioxide, and ozone on an infrared spectrum, transmittance was calculated using Lambert–Beer's law, the steady-state path radiation was precomputed according to Kirchhoff's law, and the Rayleigh and Mie scattering effects were calculated with GPU when an infrared scene was rendered in real-time. Simulations were conducted to verify the performance of the proposed method by comparing our results with those obtained from the MODTRAN program. ? 2021 Elsevier B.V.
Accession Number: 20210609891557
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Record 206 of
Title:A Supervised Segmentation Network for Hyperspectral Image Classification
Author(s):Sun, Hao(1,2); Zheng, Xiangtao(3); Lu, Xiaoqiang(3)
Source: IEEE Transactions on Image Processing Volume: 30 Issue: DOI: 10.1109/TIP.2021.3055613 Published: 2021
Abstract:Recently, deep learning has drawn broad attention in the hyperspectral image (HSI) classification task. Many works have focused on elaborately designing various spectral-spatial networks, where convolutional neural network (CNN) is one of the most popular structures. To explore the spatial information for HSI classification, pixels with its adjacent pixels are usually directly cropped from hyperspectral data to form HSI cubes in CNN-based methods. However, the spatial land-cover distributions of cropped HSI cubes are usually complicated. The land-cover label of a cropped HSI cube cannot simply be determined by its center pixel. In addition, the spatial land-cover distribution of a cropped HSI cube is fixed and has less diversity. For CNN-based methods, training with cropped HSI cubes will result in poor generalization to the changes of spatial land-cover distributions. In this paper, an end-to-end fully convolutional segmentation network (FCSN) is proposed to simultaneously identify land-cover labels of all pixels in a HSI cube. First, several experiments are conducted to demonstrate that recent CNN-based methods show the weak generalization capabilities. Second, a fine label style is proposed to label all pixels of HSI cubes to provide detailed spatial land-cover distributions of HSI cubes. Third, a HSI cube generation method is proposed to generate plentiful HSI cubes with fine labels to improve the diversity of spatial land-cover distributions. Finally, a FCSN is proposed to explore spectral-spatial features from finely labeled HSI cubes for HSI classification. Experimental results show that FCSN has the superior generalization capability to the changes of spatial land-cover distributions. ? 1992-2012 IEEE.
Accession Number: 20210809947554
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Record 207 of
Title:Simulation of non-line-of-sight imaging system based on the light-cone transform
Author(s):Zhu, Wenhua(1,2); Tan, Jingjing(1,2); Ma, Caiwen(1); Su, Xiuqin(1)
Source: Proceedings of SPIE - The International Society for Optical Engineering Volume: 11761 Issue: DOI: 10.1117/12.2586651 Published: 2021
Abstract:Non-line-of-sight (NLOS) imaging is an emerging technique, which can observe objects obscured by occluders. Thanks to the improvement of optical configurations, it is receiving growing interest from researchers. In this paper, we reconstruct both 2D and 3D images by adopting the light-cone transform and validated on simulated data. Numerical results are evaluated by structural similarity index (SSIM). The results showed the good performance of the algorithm in preserving the details of 2D image and reconstruction of 3D image. The structural similarity index of the reconstructed image and the reference image is more than 50%, the target is hence being identified. This work contributes to the construction of the real system. ? COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.
Accession Number: 20210509874590
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Record 208 of
Title:Correction of the error induced by obscurations of Ritchey-Chretien collimators for high-resolution space camera MTF measured with the ISO 12233 slanted-edge method
Author(s):Liu, Shangkuo(1,2); Liu, Kai(1); E, Kewei(1); Wang, Tao(1); Li, Zhaohui(1); Yao, Baoli(1)
Source: Optik Volume: 235 Issue: DOI: 10.1016/j.ijleo.2021.166653 Published: June 2021
Abstract:We propose a method to correct the error induced by the obscurations of Ritchey-Chretien (R-C) collimators, when measuring modulation transfer function (MTF) of high-resolution space cameras by the ISO 12,233 slanted-edge method. The obscurations of an R-C collimator include the secondary mirror (SM) and its supporting bars. Mathematical models are derived to simulate possible obscurations by virtual surfaces of Zemax, with which we get the correction function (CF) of the obscuration induced error (OIE). Simulated results manifest that the proposed method can correct the OIE. Furthermore, an experiment setup is established with the same system parameters of the previous Zemax modeled system. The experiment results verify the effectiveness of the proposed method again. Our method can guarantee the precision of the ISO 12,233 slanted-edge method when an R-C collimator is chosen. ? 2021 Elsevier GmbH
Accession Number: 20211010037844
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Record 209 of
Title:Digital micromirror device based ptychographic phase microscopy
Author(s):Zheng, Juanjuan(1,2,3); Wen, Kai(1); Gao, Zhaolin(1); Zalevsky, Zeev(4); Gao, Peng(1)
Source: Optics Communications Volume: 498 Issue: DOI: 10.1016/j.optcom.2021.127218 Published: November 1, 2021
Abstract:In this paper, ptychographic phase microscopy (PPM) with digital illumination addressing via a digital micromirror device (DMD) was demonstrated. A moving circular pattern is sequentially lighted up by a DMD and projected on the sample for illumination stepping, and a CCD camera records the generated diffraction patterns. Then, the quantitative phase distribution of the sample can be reconstructed from the diffraction patterns by using an iterative algorithm. Compared with conventional PPM approaches, this method has a fundamentally enhanced imaging speed due to the usage of the digital scan to replace the conventional mechanical scan. Furthermore, parallelized illumination strategy, which loads multiple pupils to DMD simultaneously, is used to further improve the imaging speed to 0.8 s per phase image. We envisage that this method will contribute to high-contrast, quantitative phase imaging of transparent samples without labeling. ? 2021 Elsevier B.V.
Accession Number: 20212710587204
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Record 210 of
Title:Semantics-consistent representation learning for remote sensing image-voice retrieval
Author(s):Ning, Hailong(1,2,3); Zhao, Bin(4); Yuan, Yuan(4)
Source: arXiv Volume: Issue: DOI: null Published: March 9, 2021
Abstract:With the development of earth observation technology, massive amounts of remote sensing (RS) images are acquired. To find useful information from these images, cross-modal RS image-voice retrieval provides a new insight. This paper aims to study the task of RS image-voice retrieval so as to search effective information from massive amounts of RS data. Existing methods for RS image-voice retrieval rely primarily on the pairwise relationship to narrow the heterogeneous semantic gap between images and voices. However, apart from the pairwise relationship included in the datasets, the intra-modality and non-paired inter-modality relationships should also be taken into account simultaneously, since the semantic consistency among non-paired representations plays an important role in the RS image-voice retrieval task. Inspired by this, a semantics-consistent representation learning (SCRL) method is proposed for RS image-voice retrieval. The main novelty is that the proposed method takes the pairwise, intra-modality, and non-paired inter-modality relationships into account simultaneously, thereby improving the semantic consistency of the learned representations for the RS image-voice retrieval. The proposed SCRL method consists of two main steps: 1) semantics encoding and 2) semantics-consistent representation learning. Firstly, an image encoding network is adopted to extract high-level image features with a transfer learning strategy, and a voice encoding network with dilated convolution is devised to obtain high-level voice features. Secondly, a consistent representation space is conducted by modeling the three kinds of relationships to narrow the heterogeneous semantic gap and learn semantics-consistent representations across two modalities. Extensive experimental results on three challenging RS image-voice datasets, including Sydney, UCM and RSICD image-voice datasets, show the effectiveness of the proposed method. ? 2021, CC BY.
Accession Number: 20210074510
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Record 211 of
Title:Ultra-broadband Bragg concave diffraction grating designs on 220-nm SOI for wavelength demultiplexing
Author(s):Li, Ke(1); Zhu, Jingping(1); Duan, Qihang(2,3); Sun, Yuzhou(1); Hou, Xun(1,2)
Source: Optics Express Volume: 29 Issue: 19 DOI: 10.1364/OE.431133 Published: September 13, 2021
Abstract:The appropriate broadband design of a de/multiplexer can significantly increase the channel number and consequently the transmission capacity of a wavelength division multiplexing system. Herein, we present the first ultra-broadband Bragg concave diffraction grating (CDG) on a 220-nm silicon-on-insulator, covering most of the E, S, C, L, and U telecommunication wavebands spanning from 1.425 to 1.675 μm. A wide-band-gap Bragg mirror is employed to facilitate broadband reflection, with a low diffraction order of grating for a sufficient free spectral range. Numerical simulations show that the proposed approaching blazed concave diffraction grating (AB-CDG) for the two-material case exhibits a high integration, simple fabrication process, and promising spectral performance. We fabricate the grating for design verification with a low transmission loss of -0.6 dB and a crosstalk below -33.7 dB for the eight measured wavelength channels covering the spectral range from 1.5 to 1.61 μm that is limited by the bandwidth of the grating coupler. This design can be used for broadband wavelength demultiplexing, frontier astronomical observation, and spectroscopic imaging. ? 2021 Optical Society of America under the terms of the OSA Open Access Publishing Agreement.
Accession Number: 20213710879678
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Record 212 of
Title:Energy-Efficient Design for a NOMA assisted STAR-RIS Network with Deep Reinforcement Learning
Author(s):Guo, Yi(1); Fang, Fang(2); Cai, Donghong(3); Ding, Zhiguo(4)
Source: arXiv Volume: Issue: DOI: null Published: November 30, 2021
Abstract:Simultaneous transmitting and reflecting reconfigurable intelligent surfaces (STAR-RISs) has been considered as a promising auxiliary device to enhance the performance of the wireless network, where users located at the different sides of the surfaces can be simultaneously served by the transmitting and reflecting signals. In this paper, the energy efficiency (EE) maximization problem for a non-orthogonal multiple access (NOMA) assisted STAR-RIS downlink network is investigated. Due to the fractional form of the EE, it is challenging to solve the EE maximization problem by the traditional convex optimization solutions. In this work, a deep deterministic policy gradient (DDPG)-based algorithm is proposed to maximize the EE by jointly optimizing the transmission beamforming vectors at the base station and the coefficients matrices at the STAR-RIS. Simulation results demonstrate that the proposed algorithm can effectively maximize the system EE considering the time-varying channels. Copyright ? 2021, The Authors. All rights reserved.
Accession Number: 20210405463
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Record 213 of
Title:Method to Improve the Detection Accuracy of Quadrant Detector Based on Neural Network
Author(s):Wang, Xuan(1); Su, Xiuqin(2); Liu, Guizhong(3); Han, Junfeng(2); Zhu, Wenhua(2); Liu, Zengxin(2)
Source: IEEE Photonics Technology Letters Volume: 33 Issue: 22 DOI: 10.1109/LPT.2021.3116240 Published: November 15, 2021
Abstract:The quadrant detector (QD), has developed into a core detector in the free space optical communication system. The light power received by the detector surface will be very weak after long distance transmission of laser, it brings great challenges to the high precision spot position detection of the detector. Therefore, this letter proposes a method to improve the spot position detection accuracy of the QD through artificial neural network. The neural network can solve the impact of multiple different factors on the detection accuracy of the detector at one time, which can save a lot of time and cost. Moreover, the test results of the detection accuracy of the network show that the neural network has significantly improved the detection accuracy of the spot position of the QD. ? 1989-2012 IEEE.
Accession Number: 20214111016202
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Record 214 of
Title:Spectral Characteristics of Fiber-Based S-Shape Taper Refractometer with High Sensitivity
Author(s):Ma, Jianwen(1); Cheng, Haihao(2); Yang, Xuemei(1); Zhang, Songyang(1); Li, Yongqi(1); Wang, Shun(1); Wu, Shun(1)
Source: IEEE Photonics Technology Letters Volume: 33 Issue: 22 DOI: 10.1109/LPT.2021.3115955 Published: November 15, 2021
Abstract:In this work, we have experimentally demonstrated the refractive index (RI) sensing characteristics of a S-shape taper refractometer (STR) based on modal interference theory. Our preliminary theoretical analysis reveals that there exists a critical cladding mode, which is essential for understanding the sensing characteristics. When the dominant cladding mode involved in a core-cladding interference is close to the critical cladding mode, the resulting RI sensitivity tends to reach a maximum value. Moreover, both the critical and the dominant cladding mode are dependent on ambient RI. Our sensor achieves a high RI sensitivity of 2109.7 nm/RIU for a transmission dip at around 1505 nm with a measurement range of 1.36 to 1.39. ? 1989-2012 IEEE.
Accession Number: 20214211026817
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Record 215 of
Title:A wide-band collimator with large field of view and low distortion
Author(s):Zhang, Xuemin(1); Dai, Yidan(2); Song, Xing(1); Li, Hua(1)
Source: Proceedings of SPIE - The International Society for Optical Engineering Volume: 11780 Issue: DOI: 10.1117/12.2588832 Published: 2021
Abstract:With the continuous development of aerospace and aviation, the field of view of the interferometric spectrometer is getting larger and larger, and the field of view of the interferometer also increases. In order to realize the precise adjustment of the interferometer, it is necessary to input the interferometer through a large field of view target to form a large array of interference fringes. In order to improve the measurement accuracy of interference fringes, the large field of view target with small distortion and small chromatic aberration is required to produce interference fringes with a large field of view, so it is necessary to design wide-band collimator with a large field of view to provide an object that meets the above characteristics. In this paper, we designed a collimator whose focal length of the system is 307mm, the field of view is ±12°, the working wavelength is 450nm~900nm,the effective aperture is F50mm. The diameter of the diffusion spot in each field of view is smaller than the diameter of the Ellie disk, reaching the diffraction limit, and the distortion correction is better than 2%. The transfer function is almost close to the diffraction limit, meeting the design requirements of the wide-band collimator with large field of view and low distortion. ? 2021 SPIE.
Accession Number: 20211410174068
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Record 216 of
Title:Research on the Quantitative Analysis Method of Nitrate in Complex Water by Full Scale Spectrum With GS-SVR
Author(s):Lei, Hui-Ping(1,2); Hu, Bing-Liang(1); Yu, Tao(1); Liu, Jia-Cheng(1); Li, Wei(1,2); Wang, Xue-Ji(1); Zou, Yan(3); Shi, Qian(3)
Source: Guang Pu Xue Yu Guang Pu Fen Xi/Spectroscopy and Spectral Analysis Volume: 41 Issue: 2 DOI: 10.3964/j.issn.1000-0593(2021)02-0372-07 Published: February 2021
Abstract:Nitrate is an important index of water quality monitoring. The high concentration of nitrate in water results in the decrease of biodiversity and the degradation of the ecosystem. Meanwhile, it will cause irreversible harm to human health. Water quality monitoring technology based on the spectrum is the trend of modern water environment monitoring. Compared with the traditional method, nitrate field sampling and laboratory analysis, it has the advantages of simple operation, no pretreatment, fast detection, good repeatability and no pollution. Due to the complexity and diversity of water components, there is a high degree of nonlinearity between water parameters and absorbance. Traditional linear regression prediction models are not applicable, such as single wavelength method, dual wavelength method and partial least square method. Therefore, this paper proposes a new method for the determination of nitrate in water by fine full spectrum combined with the improved variable step grid search algorithm optimized support vector regression (GS-SVR). In cooperation with the college of chemistry and chemical engineering of Shaanxi University of Science and Technology, 94 groups of solution samples with different concentrations were prepared according to different concentration gradients and the experimental requirements by using standard nitrate solution, platinum cobalt standard solution and formazine standard suspension. Firstly, the transmittance spectrum was converted to absorbance, and 94 solution samples were divided into 80 training sets and 14 test sets by Kennard stone algorithm. Secondly, the improved GS algorithm combined with 5-fold cross validation is used to optimize the parameters of SVR by reducing the search range and changing the search step for many times, and the optimal penalty parameters and kernel function width are used to build model, which is used to predict the test set. Meanwhile, the prediction results are compared with those of BPNN, SVR, GS-SVR, PSO-SVR and GA-SVR. The results show that the coefficient of determination R2=0.993 5, root means square of prediction RMSEP=0.043 5. The optimal parameters are (512, 0.044 2), and the average training time is 13 s. Compared with the above five prediction models, R2 increased by 1.22%, 11.66%, 0.78%, 0.74%, 0.77%, training efficiency increased by 4.15 times (BPNN), 8.30 times (GS-SVR), 21.38 times (PSO-SVR), 10.23 times (GA-SVR). The prediction accuracy and training efficiency of the model has been greatly improved, which provides a novel approach basis for rapid and real-time online monitoring of nitrate concentration in the complex water body. This method is also suitable for the establishment prediction models of other water quality parameters. ? 2021, Peking University Press. All right reserved.
Accession Number: 20210609892037
