Dr. Jing Xu Profile

Dr. Jing Xu

at Beijing Institute of Space Mechanics & Electricity

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Publications (7)

Proceedings Article | 12 March 2021 Paper

Evaluation criteria for computational spectral imaging quality

Jing Xu, Yun Su, Haibo Zhao, Yanli Liu, Xiaoming Zhong, Xiaojie Yu

Proceedings Volume 11763, 1176331 (2021) https://doi.org/10.1117/12.2586465

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Proceedings Article | 12 March 2021 Paper

Study on returned signal spatial distribution and detection ability of laser bathymetric system

Song Yang, Shixiang Cao, Jinghao Zhang, Xuling Lin, Jing Xu, Zhenmin Shen, Qian Sun, Zhiqiang Wu, Weidong Shang, Yongchao Zheng

Proceedings Volume 11763, 117634I (2021) https://doi.org/10.1117/12.2586999

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Proceedings Article | 12 March 2021 Paper

Stable imaging of space optical camera with high resolution and large field of view

Jing Xu, Yun Su, Yue Yu, Song Yang

Proceedings Volume 11763, 117632Y (2021) https://doi.org/10.1117/12.2586450

KEYWORDS: Image restoration, Cameras, Point spread functions, Imaging systems, Image resolution, Astronomical imaging, Optical design, Atmospheric optics, Optical imaging, Mirrors

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Proceedings Article | 5 November 2020 Paper

Diffractive optical imaging spectrometer with reference channel

Haibo Zhao, Yanli Liu, Xiaojie Yu, Jing Xu, Yechao Wang, Lisha Zhang, Xiaoming Zhong, Fang Xue, Quansen Sun

Proceedings Volume 11566, 115660S (2020) https://doi.org/10.1117/12.2580407

KEYWORDS: Imaging systems, Diffraction, Spectroscopy, Multichannel imaging systems, Imaging spectroscopy, Demodulation, Optical imaging, Signal detection

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Proceedings Article | 5 November 2020 Paper

Research on snapshot infrared computational spectral imaging technology

Yanli Liu, Haibo Zhao, Dunliang Shen, Jing Xu, Fang Xue, Xiaoming Zhong, Xiaojie Yu

Proceedings Volume 11563, 115630Q (2020) https://doi.org/10.1117/12.2580389

KEYWORDS: Infrared radiation, Infrared imaging, Imaging spectroscopy, Sensors, Infrared spectroscopy, Spectroscopy, Imaging systems, Infrared sensors, Prisms

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Proceedings Article | 5 November 2020 Paper

New spectral polarization imaging system based on optical fiber imaging

Haibo Zhao, Yanli Liu, Xiaojie Yu, Jing Xu, Yechao Wang, Lisha Zhang, Xiaoming Zhong, Fang Xue

Proceedings Volume 11567, 115674F (2020) https://doi.org/10.1117/12.2580378

KEYWORDS: Polarization, Imaging systems, Optical fibers, Sensors, Optical imaging, Target detection, Spectrometers

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Proceedings Article | 5 November 2020 Paper

Dual channel snapshot compressive spectral polarization imaging technology

Yanli Liu, Haibo Zhao, Dunliang Shen, Yechao Wang, Xiaoming Zhong, Xiaojie Yu, Jing Xu

Proceedings Volume 11566, 115660O (2020) https://doi.org/10.1117/12.2580127

KEYWORDS: Polarization, Sensors, Reconstruction algorithms, Imaging systems, Imaging technologies, Image quality, Spectral resolution, Polarizers, Optical engineering

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The spectral polarization imager can detect the spectral polarization information of the target reflection or radiated light that cannot be obtained by ordinary optical instruments. The obtained spectral polarization image can provide richer target information than the intensity image and the spectral image. At the same time, being able to achieve snapshot imaging and improve the spectral resolution is the research and development direction of polarization spectrum imaging technology. In this paper, we present a dual channel snapshot compressive spectral polarization imaging technique for simultaneous acquisition of two-dimensional intensity information, one-dimensional spectral information, and four-dimensional polarization information of a target in visible range. One channel is based on a coded mask and micro-polarizer array, and one channel is based on a pixel-level polarizer array detector. The main optical path replaces the ordinary detector with a micro-polarizer array based on CASSI. The micro-polarizer array consists of 0°, 45°, 90°, and 135° linear micro-polarizers regularly distributed, and each pixel matches the pixel of the detector. The three Stokes parameters of the scene are compressed and sensed, and a four-dimensional (4D) data cube is projected onto a two-dimensional (2D) focal plane. Through nonlinear optimization with sparsity constraints, a 4D spectral polarization data cube is reconstructed from 2D measurements. The addition of a pixel-level polarizer array detector helps to improve the measurement accuracy of spectral information and polarization information. Optical experimental results confirm that the architecture reduces the total number of measurements required to obtain a spectrally polarized image compared to traditional acquisition methods. The dual channel combination enables simultaneous acquisition of spectral and polarization information, and improves the quality of reconstructed image based on compressed sensing algorithm. A dual-channel experimental device with coded aperture spectral polarization imaging channel and polarization imaging channel was set up to obtain spectral data cubes with 4 polarization states in 25 bands in the range of 450nm-650nm, and the polarization degree and polarization angle of each band. The spectral resolution was better than 10nm, and the spectral restoration accuracy was about 86.3%. Compared with the single-channel imaging method, the spectral reconstruction accuracy was improved by 10.5%.This has guiding significance for the design and research of light and miniaturized hyperspectral polarization imagers in the future. It is expected to be widely used in astronomical observation, atmospheric detection, biomedical diagnosis, earth environment monitoring, target detection and identification and other fields.

Showing 5 of 7 publications

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