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Terahertz Security Image Quality Assessment by No-reference Model Observers

  • Menghan HuEmail author
  • Xiongkuo Min
  • Wenhan Zhu
  • Yucheng Zhu
  • Zhaodi Wang
  • Xiaokang Yang
  • Guang Tian
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 815)

Abstract

To provide the possibility of developing objective image quality assessment (IQA) algorithms for THz security images, we constructed the THz security image database (THSID) including a total of 181 THz security images. Subsequently, the existing no-reference IQA algorithms, which were 5 opinion-aware approaches viz., NFERM, GMLF, DIIVINE, BRISQUE and BLIINDS2, and 8 opinion-unaware approaches viz., QAC, SISBLIM, NIQE, FISBLIM, CPBD, S3 and Fish_bb, were executed for the evaluation of the THz security image quality. The statistical results demonstrated the superiority of Fish_bb over the other testing IQA approaches for assessing the THz image quality with PLCC (SROCC) values of 0.8925 (−0.8706), and with RMSE value of 0.3993. The linear regression analysis and Bland-Altman plot further verified that the Fish_bb could substitute for the subjective IQA. Nonetheless, for the classification of THz security images, we tended to use S3 as a criterion for ranking THz security image grades because of the relatively low false positive rate in classifying bad THz image quality into acceptable category (24.69%). Interestingly, due to the specific property of THz image, the average pixel intensity gave the best performance than the above complicated IQA algorithms, with the PLCC, SROCC and RMSE of 0.9001, −0.8800 and 0.3857, respectively. This study will help the users such as researchers or security staffs to obtain THz security images of good quality. Currently, our research group is attempting to make this research more comprehensive.

Keywords

Terahertz security image quality assessment THz image database  THz imaging technique Blind image quality assessment  THz security device 

Notes

Acknowledgements

The work is supported by MOST under 2015BAK05B03. The authors would like to acknowledge the staffs working in BOCOM Smart Network Technologies Inc., who assisted in acquiring the THz images.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • Menghan Hu
    • 1
    Email author
  • Xiongkuo Min
    • 1
  • Wenhan Zhu
    • 1
  • Yucheng Zhu
    • 1
  • Zhaodi Wang
    • 1
  • Xiaokang Yang
    • 1
  • Guang Tian
    • 2
  1. 1.Shanghai Institute for Advanced Communication and Data Science, Shanghai Key Laboratory of Digital Media Processing and TransmissionShanghai Jiao Tong UniversityShanghaiPeople’s Republic of China
  2. 2.BOCOM Smart Network Technologies Inc.ShanghaiPeople’s Republic of China

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