Bingliang Hu

Xi'an Institute of Optics and Precision Mechanics

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i-10 index

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Zhoufeng Zhang

Xi'an Institute of Optics and Precision Mechanics

Xuebin Liu

Xi'an Institute of Optics and Precision Mechanics

Quan Wang

Xi'an Institute of Optics and Precision Mechanics

Ruochen Dang

Xi'an Institute of Optics and Precision Mechanics

Haiwei Li

Xi'an Institute of Optics and Precision Mechanics

Liyao Song

Xi'an Technological University

Quan Wang

Xi'an Institute of Optics and Precision Mechanics

Yutao Feng

Xi'an Institute of Optics and Precision Mechanics

Siyuan Li

Xi'an Institute of Optics and Precision Mechanics

Jian Du

Xi'an Institute of Optics and Precision Mechanics

Cooperative Institutions

Chinese Academy of Sciences

280

Xi'an Institute of Optics and Precision Mechanics

219

University of Chinese Academy of Sciences

174

Xi'an Jiaotong University

Shanghai Institute of Optics and Fine Mechanics

Shanghai Jiao Tong University

Zhejiang University

Central South University

University of Science and Technology of China

Sichuan University

Author Statistics

Papers

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Sanxingdui Cultural Relics Recognition Algorithm Based on Hyperspectral Multi-Network Fusion

Computers, materials & continua/Computers, materials & continua (Print) (2023)

Shi Qiu Pengchang Zhang Xingjia Tang Zimu Zeng Miao Zhang

Sanxingdui cultural relics are the precious cultural heritage of humanity with high values of history, science, culture, art and research. However, mainstream analytical methods are contacting and detrimental, which is unfavorable to the protection of cultural relics. This paper improves the accuracy of the extraction, location, and analysis of artifacts using hyperspectral methods. To improve the accuracy of cultural relic mining, positioning, and analysis, the segmentation algorithm of Sanxingdui cultural relics based on the spatial spectrum integrated network is proposed with the support of hyperspectral techniques. Firstly, region stitching algorithm based on the relative position of hyper spectrally collected data is proposed to improve stitching efficiency. Secondly, given the prominence of traditional HRNet (High-Resolution Net) models in high-resolution data processing, the spatial attention mechanism is put forward to obtain spatial dimension information. Thirdly, in view of the prominence of 3D networks in spectral information acquisition, the pyramid 3D residual network model is proposed to obtain internal spectral dimensional information. Fourthly, four kinds of fusion methods at the level of data and decision are presented to achieve cultural relic labeling. As shown by the experiment results, the proposed network adopts an integrated method of data-level and decision-level, which achieves the optimal average accuracy of identification 0.84, realizes shallow coverage of cultural relics labeling, and effectively supports the mining and protection of cultural relics.

Image stitching

Position (finance)

10.32604/cmc.2023.042074

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Citations (2)

Phase error correction in Fourier transform spectrometer based on phase correlation

Bingliang Hu

Phase error correction(PEC) is an important step during hyperspectral data processing of the Fourier transform spectrometer.We present a new method for phase correction of the Fourier transform data according to the symmetry of interference curve and the calculation of phase correlation method.The phase correlation is fitted to Sinc function,the sub-pixel offset is calculated,and the interference curve is converted into spectral domain through discrete cosine transform(DCT).The interference data simulated by DCT is compared with the data by Mertz method,and the results shows that the proposed method has higher correction accuracy than Mertz and simple calculation.

Sinc function

Phase correlation

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Comprehensive design analysis and verification of space-based short-wave infrared coded spectrometer via curved prism dispersion

Applied Optics (2022)

Xinyin Jia Xi-Jie Li Bingliang Hu Libo Li Fei-Cheng Wang

The spaceborne dispersive spectrometer is widely used in environmental, resource, and ocean observations. The coded spectrometer has higher energy advantages than the dispersion spectrometer, so it has great application prospects. In the current study, we developed an off-axis short-wave infrared coded optical system (SICOS) based on curved prism dispersion, and we further explored the design and optimization of the SICOS structure. Finite element analyses of a space-based short-wave infrared coded spectrometer based on curved prism dispersion (SSICS-CPD), including static simulation, modal analysis, sinusoidal vibration mechanical analysis, and random vibration mechanical analysis, were carried out. Simulation results showed that the SICOS support structure had excellent mechanical and thermal stability. As off-axis optical systems cannot meet the requirements of optical position accuracy through centering processing, a point source microscope and three-coordinate measuring machines were employed to complete the high-precision and rapid assembly of the SSICS-CPD. In addition, verification tests of surface shape error, stress relief, random vibration, and optical design parameters were carried out to validate the high stability and imaging performance of the SSICS-CPD. Results showed that the average modulation transfer function in the full field was 0.43 at 16.67 lp/mm, the spectral smile was <0.2 pixels, and the spectral keystone was <0.1 pixels. The design, analysis, assembly, and verification of the SSICS-CPD provide a useful reference for the development of other spaceborne prism dispersion spectrometers.

Prism

Imaging spectrometer

10.1364/ao.449320

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Citations (2)

Large-Scale Stitching of Hyperspectral Remote Sensing Images Obtained from Spectral Scanning Spectrometers Mounted on Unmanned Aerial Vehicles

Electronics (2025)

Hong Liu Bingliang Hu Xingsong Hou Tao Yu Zhoufeng Zhang

To achieve large-scale stitching of the hyperspectral remote sensing images obtained by unmanned aerial vehicles (UAVs) equipped with an acousto-optic tunable filter spectrometer, this study proposes a method based on a feature fusion strategy and a seam-finding strategy using hyperspectral image classification. In the feature extraction stage, SuperPoint deep features from images in different spectral segments of the data cube were extracted and fused. The feature depth matcher, LightGlue, was employed for feature matching. During the data cube fusion stage, unsupervised K-means spectral classification was performed separately on the two hyperspectral data cubes. Subsequently, grayscale transformations were applied to the classified images. A dynamic programming method, based on a grayscale loss function, was then used to identify seams in the transformed images. Finally, the identified splicing seam was applied across all bands to produce a unified hyperspectral data cube. The proposed method was applied to hyperspectral data cubes acquired at specific waypoints by UAVs using an acousto-optic tunable filter spectral imager. Experimental results demonstrated that the proposed method outperformed both single-spectral-segment feature extraction methods and stitching methods that rely on seam identification from a single spectral segment. The improvement was evident in both the spatial and spectral dimensions.

Image stitching

Imaging spectrometer

Full spectral imaging

10.3390/electronics14030454

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FBLSTM: A Filter-Bank LSTM-based deep learning method for MI-EEG classification

Yawei Gui Ziwei Tian Xi Liu Bingliang Hu Quan Wang

Motor imagery electroencephalogram (MI-EEG) classification is a vital task for brain computer interface (BCI) system. But the classification accuracy is not satisfactory, which hinders its generalizability. This study proposes a Filter-Bank Long Short-Term Memory (LSTM) Network (FBLSTM), which adopts a series of band-pass filters to obtain the different frequency information in EEG signals, and a convolution neural network to obtain spatial information. Moreover, a LSTM with attention mechanism is employed to process time series information. The open BCI Competition IV dataset 2a is applied to validate the performance of the proposed FBLSTM. Compared with recent methods, our method shows advantages on the within-subject and cross-subject 4-class classification performance and outperformed existing models, achieving an average accuracy of 72.4% and 53.6%, respectively.

Motor Imagery

Filter bank

Convolution (computer science)

10.1117/12.2673936

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Design of a high aperture compression ratio, dual-band static Fourier transform imaging spectrometer for remote sensing

Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE (2014)

Chunbo Zou Bingliang Hu Libo Li Qinglan Bai Xin Sun

A novel dual-band static Fourier transform imaging spectrometer was designed, which was the spatio-temporally modulated imaging Fourier transform spectrometer based on Sagnac interferometer. The approach represented a simplification and mass reduction over the traditional approach. It could obtain two-dimensional spatial images and one dimensional spectral image in two bands simultaneously. The two bands was separated through a dichroic prism and imaging in two detectors. one band was the visible and near infrared band, with the spectral range 400nm-1000nm and spectral resolution 187.5 wave numbers; the other was the short wave infrared band, with the spectral range 1000nm- 2500nm and spectral resolution 150 wave numbers. To reduce the size of the Interferometer, a high aperture compression ratio telescope system was designed before. The optical aperture was compressed to 1/10, and the volume of interferometer was reduced to 1/1000. For the convenience of engineering implementation, the telescope was composed of two no-aberration object lens: fore-lens and Collimating lens. The two band imaging spectrometers shared the primary lens and the second lens of the fore-lens and use their own collimating lens, interferometers and Fourier transform lens. The collimating lens and the Fourier transform lens of each spectrometer could be designed to the same structural style and parameters. The both spectrometers had a focal length of 1000mm, F number of 5, FOV(field of view) of 1°. Moreover, both image qualities were close to the diffraction limit, the distortion was less than 2%. The advantage of the instrument was that dual band spectral image could be acquired at the same time and the interferometer was miniaturized extremely in the case of unchanged technical indicators.

Imaging spectrometer

Multi-band device

Aperture (computer memory)

10.1117/12.2083243

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Citations (2)

Design and Experimental Test of a Common-path Coherent-dispersion Spectrometer for Exoplanet Searches

Publications of the Astronomical Society of the Pacific (2019)

Ruyi Wei Shasha Chen Bingliang Hu Qiangqiang Yan Yinhua Wu

A coherent-dispersion spectrometer (CODES) system using the radial velocity (RV) method for exoplanet searches is established in this paper. This spectrometer utilizes a new Sagnac interferometer with common-path and asymmetric designs. Compared with the traditional Michelson interferometer-based spectrometer for exoplanet detection, these designs markedly improve the stability of the optical path difference (OPD) to positional changes in optical elements or air density changes, reducing the need for active cavity stabilization. Furthermore, the asymmetric Sagnac design allows convenient separation of the two complementary outputs. In order to verify the feasibility of the CODES, an optical Doppler shift experiment is constructed in the laboratory. The RV signal was extracted by the phase shifts of the interference fringes produced by the spectrometer. The experimental results show that the obtained retrieved RV is 76.7 m s−1, with an absolute error of 0.3 m s−1 compared to simulated values. And the root mean square error (RMSE) and the standard deviation (STD) are 21.3 m s−1 and 21.4 m s−1, respectively. Error analyses show that the OPD change caused by the temperature variation is the main factor for the RMSE and STD.

10.1088/1538-3873/ab503a

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Citations (8)

Graphene–Silver Hybrid Metamaterial for Tunable and High Absorption at Mid-Infrared Waveband

IEEE Photonics Technology Letters (2018)

Shun Cao Taisheng Wang Qiang Sun Yuguo Tang Bingliang Hu

We proposed a hybrid metamaterial structure based on graphene-silver, which has tunable and efficient light-absorbing performance at the mid-infrared regime. It is shown that this model can absorb light effectively with a maximum of 100% at the absorption peak wavelength. In addition, the absorption peak wavelength can be adjusted flexibly by changing parameters, including the chemical potential applied to graphene or other structural parameters of the structure. This nearly perfect absorption capability is attributed to the synergetic effects of the localized surface plasmon enhancement of Ag nanoribbon, graphene plasmonics, metal-insulator-graphene mode and Fabry-Perot resonance. This kind of tunable absorber can be used in mid-infrared photodetectors or spectroscopy fields.

10.1109/lpt.2018.2800729

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Citations (18)

Design of infrared signal processing system based on ZYNQ platform

Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE (2016)

Zhuoyu Bai H. Leng Bingliang Hu Shuang Wang

A newly developed real-time infrared signal processing system based on the heterogeneous multi-processor system on chip (MPSoC) is proposed in this paper. The architecture, hardware configuration, image pre-processing algorithms used in the system and the experimental result are presented. Compared to the infrared signal processing system in being, Xilinx Zynq-7000 All Programmable SoC has been used in the proposed system which is more portable, integrated, and has excellent performance during its signal processing.

MPSoC

SIGNAL (programming language)

10.1117/12.2246949

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Citations (1)

Intelligent Classification for Emotional Issues by Deep Learning Network on EEG Signal Processing

2022 IEEE International Conference on Electrical Engineering, Big Data and Algorithms (EEBDA) (2022)

Shaokang Yin Feiyu Zhu Xiaojie Wei Gongen Han Runqi Zhang

Identifying the risk of emotional issues is of great significance to the development of adolescents. Electroencephalography (EEG) signals can reflect brain activities, and imply the emotional status, therefore can be used to identify emotional issues. In this study, we designed an experimental paradigm for high school adolescents by displaying emotion-inducing pictures as stimuli and recorded their EEG signals simultaneously. The EEG signals was preprocessed and analyzed. In this paper we applied a convolutional network EEGNet to classify four emotional issues in adolescents: depression symptom, manic symptom, anxiety symptom and the control group. The results showed that the classification accuracy of the four groups can reach 94.24%. In addition, this paper explored using different types of picture stimuli on the classification and reached a result above chance level. This work extended the previous work on the classification of emotional issues to four categories, and achieved a good classification accuracy.

SIGNAL (programming language)

10.1109/eebda53927.2022.9744774

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Citations (3)