Low-light-level image super-resolution reconstruction based on iterative projection photon localization algorithm

Changsheng Ying; Peng Zhao; Ye Li

doi:10.1117/1.JEI.27.1.013026

23 February 2018 Low-light-level image super-resolution reconstruction based on iterative projection photon localization algorithm

Changsheng Ying, Peng Zhao, Ye Li

Author Affiliations +

Funded by: 111 Project of China, Project of China, “111” Project of China, Key Laboratories Foundation Program

Journal of Electronic Imaging, Vol. 27, Issue 1, 013026 (February 2018). https://doi.org/10.1117/1.JEI.27.1.013026

Abstract

The intensified charge-coupled device (ICCD) is widely used in the field of low-light-level (LLL) imaging. The LLL images captured by ICCD suffer from low spatial resolution and contrast, and the target details can hardly be recognized. Super-resolution (SR) reconstruction of LLL images captured by ICCDs is a challenging issue. The dispersion in the double-proximity-focused image intensifier is the main factor that leads to a reduction in image resolution and contrast. We divide the integration time into subintervals that are short enough to get photon images, so the overlapping effect and overstacking effect of dispersion can be eliminated. We propose an SR reconstruction algorithm based on iterative projection photon localization. In the iterative process, the photon image is sliced by projection planes, and photons are screened under the constraints of regularity. The accurate position information of the incident photons in the reconstructed SR image is obtained by the weighted centroids calculation. The experimental results show that the spatial resolution and contrast of our SR image are significantly improved.

Citation Download Citation

Changsheng Ying, Peng Zhao, and Ye Li "Low-light-level image super-resolution reconstruction based on iterative projection photon localization algorithm," Journal of Electronic Imaging 27(1), 013026 (23 February 2018). https://doi.org/10.1117/1.JEI.27.1.013026

Received: 7 October 2017; Accepted: 6 February 2018; Published: 23 February 2018

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