Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
Dynamic Pick and Place Trajectory of Delta Parallel Manipulator Read chapter Read first chapter

2021 | OriginalPaper | Chapter

No-Reference Quality Assessment for UAV Patrol Images of Transmission Line

Authors : Xujuan Fan, Xiancong Zhang, Jinqiang He, Yongli Liao, Dengjie Zhu

Published in: Human Centered Computing

Publisher: Springer International Publishing

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Uav patrol has gradually become the main operation mode of transmission line patrol task, however, due to the influence of the shooting mode and weather, the patrol images are inevitably distorted, resulting in quality degradation. In order to effectively evaluate the patrol image quality, this paper proposes a no-reference quality assessment method. Specifically, we first construct a dedicated patrol image quality assessment database, and then propose a no-referenced quality assessment model based on structure, texture and exposure. The experimental result shows that the method surpasses existing methods and is highly consistent with the quality labels.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
previous chapter Software Component Library Management Mechanism for Equipment Parts Service Value-Net
next chapter An Inclusive Finance Consortium Blockchain Platform for Secure Data Storage and Value Analysis for Small and Medium-Sized Enterprises
Literature
1.
Wang, Z., Bovik, A.C., Sheikh, H.R., et al.: Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Process. 13(4), 600–612 (2004)CrossRef
2.
Zhang, L., Zhang, L., Mou, X., et al.: FSIM: a feature similarity index for image quality assessment. IEEE Trans. Image Process. 20(8), 2378–2386 (2011)MathSciNetCrossRef
3.
Kim, J., Lee, S.: Deep learning of human visual sensitivity in image quality assessment framework, 1969–1977 (2017)
4.
5.
Liu, Y., Zhai, G., Gu, K., et al.: Reduced-reference Image quality assessment in free-energy principle and sparse representation. IEEE Trans. Multimedia 20(2), 379–391 (2018)CrossRef
6.
Golestaneh, S.A., Karam, L.J.: Reduced-reference quality assessment based on the entropy of DNT coefficients of locally weighted gradients, pp. 4117–4120 (2015)
7.
Kang, L., Ye, P., Li, Y., et al.: Convolutional neural networks for no-reference image quality assessment. In: 2014 IEEE Conference on Computer Vision and Pattern Recognition. IEEE (2014)
8.
Xu, J., Ye, P., Li, Q., et al.: Blind image quality assessment based on high order statistics aggregation. IEEE Trans. Image Process. 25(9), 4444–4457 (2016)MathSciNetCrossRef
9.
Ye, P., Kumar, J., Doermann, D.: Beyond human opinion scores: blind image quality assessment based on synthetic scores. In: 2014 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE (2014)
10.
Mittal, A., Moorthy, A.K., Bovik, A.C.: No-reference image quality assessment in the spatial domain. IEEE Trans. Image Process. 21(12), 4695–4708 (2012)MathSciNetCrossRef
11.
Yang, G., Liao, Y., Zhang, Q., et al.: No-reference quality assessment of noise-distorted images based on frequency mapping. IEEE Access 5(99), 23146–23156 (2017)CrossRef
12.
Golestaneh, S.A., Chandler, D.M.: No-reference quality assessment of JPEG images via a quality relevance map. IEEE Signal Process. Lett. 21(2), 155–158 (2014)CrossRef
13.
Zhan, Y., Zhang, R.: No-reference image sharpness assessment based on maximum gradient and variability of gradients. IEEE Trans. Multimedia 20(7), 1796–1808 (2018)CrossRef
14.
Saad, M.A., Bovik, A.C., Charrier, C.: blind image quality assessment: a natural scene statistics approach in the DCT domain. IEEE Trans. Image Process. 21(8), 3339–3352 (2012)MathSciNetCrossRef
15.
Gu, K., Zhai, G., Yang, X., et al.: Using free energy principle for blind image quality assessment. IEEE Trans. Multimedia 17(1), 50–63 (2014)CrossRef
16.
Moorthy, A.K., Bovik, A.C.: Blind image quality assessment: from natural scene statistics to perceptual quality. IEEE Trans. Image Process. 20(12), 3350–3364 (2011)MathSciNetCrossRef
17.
Mittal, A., Soundararajan, R., Bovik, A.C.: Making a ‘Completely Blind’ image quality analyzer. IEEE Signal Process. Lett. 20(3), 209–212 (2013)CrossRef
18.
Zhang, L., Zhang, L., Bovik, A.C.: A feature-enriched completely blind image quality evaluator. IEEE Trans. Image Process. 24(8), 2579–2591 (2015)MathSciNetCrossRef
19.
Xue, W., Zhang, L., Mou, X.: Learning without human scores for blind image quality assessment. In: 2013 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE (2013)
20.
Fang, Y., Yan, J., Li, L., et al.: No reference quality assessment for screen content images with both local and global feature representation. IEEE Trans. Image Process. 27(4), 1600 (2018)MathSciNetCrossRef
21.
Gu, K., Qiao, J., Min, X., et al.: Evaluating quality of screen content images via structural variation analysis. IEEE Trans. Visual Comput. Graph. 24(10), 2689–2701 (2018)CrossRef
22.
Yue, G., Hou, C., Zhou, T.: Blind quality assessment of tone-mapped images considering colorfulness, naturalness and structure. IEEE Trans. Ind. Electron. 66(5), 3784–3793 (2019)CrossRef
23.
Yue, G., Hou, C., Gu, K., et al.: Biologically inspired blind quality assessment of tone-mapped images. IEEE Trans. Ind. Electron. 65(3), 2525–2536 (2018)CrossRef
24.
Zhang, Y., Lin, W., Li, Q., et al.: Multiple-level feature based measure for retargeted image quality. IEEE Trans. Image Process. 27(1), 451–463 (2018)MathSciNetCrossRef
25.
Guo, X., Li, X., Li, L., et al.: An efficient image quality assessment guidance method for unmanned aerial vehicle. In: 2019 Intelligent Robotics and Applications (2019)
26.
Gu, K., Tao, D., Qiao, J.F., et al.: Learning a no-reference quality assessment model of enhanced images with big data. IEEE Trans. Neural Netw. Learn. Syst. 29(4), 1301–1313 (2018)CrossRef
27.
Scholte, H., Ghebreab, S., Waldorp, L., et al.: Brain responses strongly correlate with Weibull image statistics when processing natural images. J. Vis. 9, 29 (2009)CrossRef
28.
Ojala, T., PietikäInen, M., Harwood, D.: A comparative study of texture measures with classification based on feature distributions. Pattern Recogn. 29(1), 51–59 (1996)CrossRef
Metadata
Title
No-Reference Quality Assessment for UAV Patrol Images of Transmission Line
Authors
Xujuan Fan
Xiancong Zhang
Jinqiang He
Yongli Liao
Dengjie Zhu
Copyright Year
2021
Book
Human Centered Computing

Print ISBN: 978-3-030-70625-8

Electronic ISBN: 978-3-030-70626-5

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-3-030-70626-5_43

Premium Partner

    Image Credits