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A Subjective Assessment Method of Aerospace Image Quality Based on Human Visual System

  • Wuyuan ZhouEmail author
  • Haoting Liu
  • Chang Guo
  • Weidong Dong
  • Shuo Yang
  • Shunliang Pan
  • Guoliang Tian
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 576)

Abstract

Aiming at the problems of blur, noise and contrast distortion in aerospace images, a subjective image quality assessment method based on human visual characteristics is proposed in this paper. First, the aerospace image database with different blur, noise and contrast distortions is simulated by 3D modelling software. Second, the subjects are required to give three image quality scores based on the indexes above, respectively. Third, the correlations of three indexes’ scores are calculated by the Pearson formula and then different weights are given to the indexes based on the calculated correlation coefficient above. Finally, the modified subjective image assessment scores can be obtained by the multi-factor model. The proposed subjective evaluation model takes into account the influence of multiple factors that can show the characteristics of images comprehensively. Many experiment results have verified the correctness of the proposed method.

Keywords

Aerospace image quality Human visual characteristics Subject assessment Multi-factor model 

Notes

Acknowledgements

This work is supported by the National Natural Science Foundation of China under Grant No. 61501016 and the open project of the State Key Laboratory of Intense Pulsed Radiation Simulation and Effect under Grant No. SKLIPR1713.

Compliance with Ethical Standards

The study was approved by the Logistics Department for Civilian Ethics Committee of University of Science and Technology Beijing. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Wuyuan Zhou
    • 1
    Email author
  • Haoting Liu
    • 1
  • Chang Guo
    • 1
  • Weidong Dong
    • 2
  • Shuo Yang
    • 2
  • Shunliang Pan
    • 2
  • Guoliang Tian
    • 2
  1. 1.Beijing Engineering Research Center of Industrial Spectrum ImagingUniversity of Science and Technology BeijingBeijingChina
  2. 2.Institute of Manned Space System EngineeringBeijingChina

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