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Analysis of Image Intensifiers Halo Effect with Curve Fitting and Separation Method

  • Ling Ren
  • Feng Shi
  • Hui Guo
  • DongXu Cui
  • Yunsheng Qian
  • Honggang Wang
  • Benkang Chang
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 238)

Abstract

In order to probe into the halo effect for image intensifiers, we have deduced the fitted formula for the gray value distribution (GVD) of pixels on a centerline through the center point of halo images by the numerical theory of Gaussian curve fitting and analyzed the halo effect with the curve separation method. By the image translation processing, the approximate point spread functions (PSFs) for the halo test device and image intensifiers are obtained respectively. The results show that the GVDs of pixels on the centerline in halo images for the test device and low light level (LLL) image intensifiers all consist of two curves. One curve is the Gaussian distribution curve (GDC) and the other is a straight line with the same gray value. The straight line is regarded as the background noise. After the super second generation (Gen II+), the image intensifier is put in the halo test device. Half the width of GDC for the collected halo image is smaller than that for the third generation (Gen III) one. This research is helpful for exploring the formation mechanism of halo effect and beneficial to promote the development of the LLL night vision technology.

Keywords

Test Device Image Intensifier Numerical Theory Halo Effect Night Vision 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgment

This work was supported by the Science and Technology on Low-Light-Level Night Vision Laboratory (Grant No. J20110301) and the Research and Innovation Plan for Graduate Students of Jiangsu Higher Education Institutions, China (Grant No. CXLX11_0236).

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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Ling Ren
    • 1
    • 2
  • Feng Shi
    • 2
  • Hui Guo
    • 2
  • DongXu Cui
    • 1
  • Yunsheng Qian
    • 1
  • Honggang Wang
    • 1
  • Benkang Chang
    • 1
  1. 1.Nanjing University of Science and TechnologyNanjingChina
  2. 2.Science and Technology on low-light-level Night Vision LaboratoryXi’anChina

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