Prof. Jiying Liu Profile

Prof. Jiying Liu

at National Univ. of Defense Technology

SPIE Involvement:

Author

Publications (9)

Proceedings Article | 12 April 2023 Paper

A DCNN method for phase unwrapping

Yansen Han, Jiying Liu, Yapeng Zhan, Qi Yu

Proceedings Volume 12565, 125650K (2023) https://doi.org/10.1117/12.2661627

KEYWORDS: Interferometric synthetic aperture radar, Error analysis, General packet radio service, Neural networks, Synthetic aperture radar, Signal to noise ratio, Databases, Convolution, Computer programming, Tactical intelligence

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Proceedings Article | 16 February 2022 Paper

Encoder-decoder network with self-attention module for image restoration

Qing Jin, Qi Yu, Jiying Liu, Xintong Tan

Proceedings Volume 12083, 1208313 (2022) https://doi.org/10.1117/12.2623391

KEYWORDS: Image processing

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Proceedings Article | 12 March 2020 Paper

Performance comparison of coded apertures in push-broom hyperspectral compressed sampling imaging

Mengzhu Li, Weizheng Wang, Junli Qi, Xujian Li, Jiying Liu, Wei Wang, Wusheng Tang, Wenjun Yi, Yanfang Guo, Mengjun Zhu, Jubo Zhu

Proceedings Volume 11438, 114380E (2020) https://doi.org/10.1117/12.2542670

KEYWORDS: Coded apertures, Reconstruction algorithms, Hyperspectral imaging, Coded aperture imaging, Image quality, Imaging spectroscopy

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Proceedings Article | 19 November 2019 Paper

Super-resolution hyperspectral compressed sampling imaging by push-broom coded aperture

Mengzhu Li, Weizheng Wang, Junli Qi, Wei Wang, Jiying Liu, Wusheng Tang, Wenjun Yi, Yanfang Guo, Mengjun Zhu, Jubo Zhu, Xiujian Li

Proceedings Volume 11186, 1118613 (2019) https://doi.org/10.1117/12.2537503

KEYWORDS: Coded apertures, Super resolution, Hyperspectral imaging, Charge-coupled devices, Prisms, Image resolution, Reconstruction algorithms, Coded aperture imaging, Image restoration, Image compression

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Super-resolution hyperspectral imaging is a key technology for many applications, especially in the fields of remote sensing, military, agriculture, and geological exploration. Recovering a high resolution image needs enormous data, which puts forward very high requirements on image system hardware. Compressed sampling spectral imaging technology could well solve this problem and achieve high-resolution objects with low-resolution compressed data. In this paper, the method of a compressed sampling spectral imaging based on push-broom coded aperture and dispersion prism is proposed. A spectral aliasing image is formed when the object passing through the dispersive prism. According to the prism dispersion condition and the CCD pixel size, the visible spectrum can be divided into N spectral bands, and the measurement matrix of the coded aperture is respectively calibrated for the center wavelength of each spectral band. By controlling a stepper to implement the push broom of the coded aperture to change the measurement matrix, multiple spectral aliasing images can be obtained. The pixel size of the coded aperture becomes half of the CCD by a relay lens, which means the pixel of CCD is low-resolution for the coded aperture. The super-resolution hyperspectral image of the object is obtained by the improved LS reconstruction algorithm. Simulation results show that, the recovered hyperspectral image has twice resolution compared with the low-resolution CCD image, and the peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) increase with the increasing compressed sampling hyperspectral images. For N=31, the average PSNR and SSIM recovered from six aliasing images is 22.019 and 0.235, respectively. The average PSNR and SSIM of the recovered 31 bands are also increasing with increasing aliasing images. While the aliasing imaging is 156, The average PSNR and SSIM exceeds 38 and 0.9. This method proves that super-resolution hyperspectral imaging can be achieved by capturing less low-resolution object images.

Proceedings Article | 21 July 2017 Paper

Multi-radar super-resolution imaging based compressed sensing

Fan Ye, JiYing Liu, Jubo Zhu

Proceedings Volume 10420, 1042037 (2017) https://doi.org/10.1117/12.2281906

KEYWORDS: Super resolution

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Proceedings Article | 8 March 2017 Paper

A push-broom compressive imaging system with situ calibration function for encoding mask

Lei Wang, Zhengzheng Shao, Jiying Liu, Qianwen Nie, Hui Jia, Suian Dai, Xiaofeng Wang, Jubo Zhu, Xiujian Li

Proceedings Volume 10255, 1025508 (2017) https://doi.org/10.1117/12.2267747

KEYWORDS: Compressed sensing, Compressive imaging, Calibration, Computer programming, Imaging systems, Image resolution, Super resolution, Image restoration, Coded apertures, Light sources

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SPIE Journal Paper | 28 August 2013

Spatially adapted total variational model for synthetic aperture radar image despeckling

Huiyan Liu, Jiying Liu, Fengxia Yan, Jobo Zhu, Faming Fang

JEI, Vol. 22, Issue 03, 033019, (August 2013) https://doi.org/10.1117/12.10.1117/1.JEI.22.3.033019

KEYWORDS: Synthetic aperture radar, Speckle, Mathematical modeling, Image filtering, Image processing, Phase modulation, Mathematics, Image resolution, Data modeling, Image quality

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SPIE Journal Paper | 1 April 2010

Random phase modulation and sparse sampling-based optical imaging system

Jiying Liu, Jubo Zhu, Fengxia Yan, Zenghui Zhang

OE, Vol. 49, Issue 04, 047002, (April 2010) https://doi.org/10.1117/12.10.1117/1.3366667

KEYWORDS: Imaging systems, Phase modulation, Optical imaging, Optical sensors, Modulation, Image resolution, Spatial light modulators, Image restoration, Fourier transforms, Image processing

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Proceedings Article | 28 October 2006 Paper

Error compensation and high-precision baseline estimation in InSAR geolocation using GCPs

Jiying Liu, Jubo Zhu, Zenghui Hu, Ye Liu

Proceedings Volume 6418, 64180L (2006) https://doi.org/10.1117/12.712616

KEYWORDS: Error analysis, Interferometric synthetic aperture radar, Satellites, Interferometry, Detection and tracking algorithms, Synthetic aperture radar, Algorithm development, Doppler effect, Radar, Tantalum

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Showing 5 of 9 publications

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