Dr. Wei Wang Profile

Dr. Wei Wang

at Changsha Univ of Science & Technology

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Author

Publications (3)

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 | 19 November 2019 Paper

Influence of spatial power spectrum pattern gray-level distortion on coherent diffraction imaging reconstruction

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

Proceedings Volume 11186, 1118615 (2019) https://doi.org/10.1117/12.2537515

KEYWORDS: Reconstruction algorithms, Distortion, Phase retrieval, Coherence imaging

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