Skip to main content
SpringerLink
Log in

Unfocused Blur Assessment of SAR Images

  • Conference paper
Intelligence Science and Big Data Engineering (IScIDE 2013)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8261))

Abstract

Unfocused blur assessment is an important part of SAR image quality evaluation system. The mainlobe of unfocused point target is widened and the sidelobe is raised, leading to broadened edges in the azimuth direction. Based on this phenomenon, we proposed a new method to evaluate the extent of unfocused blur using truncated image spectrum and the average edge width in the salient area. A new metric UBE is defined and verified by experiments.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Oliver, C., Quegan, S.: Understanding Synthetic Aperture Radar Images. SciTech Publishing, Inc., Raleigh (2004)

    Google Scholar 

  2. Jung, C.H., Choi, M.S., Kwag, Y.K.: Parameter Based SAR Simulator for Image Quality Evaluation. In: IEEE International Geoscience and Remote Symposium, pp. 1599–1602. IEEE Press, New York (2007)

    Google Scholar 

  3. Yitzhaky, Y., Kopeika, N.S.: Identification of Blur Parameters from Motion Blurred Images. In: Graphical Models and Image Processing, pp. 310–320 (1997)

    Google Scholar 

  4. Zhang, R., Yang, J.C., Zhang, Q., Liu, Z.K.: Motion Blur Extent Evaluation of SAR images. Acta Electronica Sinca 35(10), 2019–2022 (2007)

    MathSciNet  Google Scholar 

  5. Chang, M.M., Tekalp, A.M., Erdem, A.T.: Blur Identification Using the Bispectrum. IEEE Transactions on Acoust, Speech, Signal Processing 39, 2323–2325 (1991)

    Article  Google Scholar 

  6. Moghaddam, M.E., Jamzad, M.: Motion Blur Identification in Noisy Images using Mathematical Models and Statistical Measures. Pattern Recognition Society 40, 1946–1957 (2007)

    Article  MATH  Google Scholar 

  7. Ji, H., Liu, C.Q.: Motion Blur Identification from Image Gradients. In: IEEE Conference on Computer Vision and Pattern Recogniton, pp. 1–8. IEEE Press, New York (2008)

    Google Scholar 

  8. Gilles, S.: Robust Description and Matching of Images. University of Oxford Press (1998)

    Google Scholar 

  9. Sheikh, H.R., Bovik, A.C., Cormack, L., Wang, Z.: LIVE Image Quality Assessment Database (2003), http://live.ece.utexas.edu/research/quality

Download references

Author information

Authors and Affiliations

  1. Northwest Institute of Nuclear Technology, 710024, Xi’an, China

    Han Zhang, Weidong Yan, Hui Bian, Weiping Ni, Junzheng Wu, Sha Li, Xinlu Ma & Ying Lu

Authors
  1. Han Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Weidong Yan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hui Bian
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Weiping Ni
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Junzheng Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Sha Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Xinlu Ma
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Ying Lu
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. School of Automation and Electrical Engineering, University of Science and Technology, Xueyuan Road No. 30, 100083, Beijing, China

    Changyin Sun

  2. Department of Psychology, Peking University, Yiheyuan Road No. 5, 100871, Beijing, China

    Fang Fang

  3. Department of Computer Science and Technology, Nanjing University, Xianlin Avenue No. 163, 210023, Nanjing, China

    Zhi-Hua Zhou

  4. School of Automation, Southeast University, Sipailou No. 2, 210096, Nanjing, China

    Wankou Yang

  5. Institute of Automation, Chinese Academy of Sciences, No. 95 East Zhongguancun Road, 100190, Beijing, China

    Zhi-Yong Liu

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Zhang, H. et al. (2013). Unfocused Blur Assessment of SAR Images. In: Sun, C., Fang, F., Zhou, ZH., Yang, W., Liu, ZY. (eds) Intelligence Science and Big Data Engineering. IScIDE 2013. Lecture Notes in Computer Science, vol 8261. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-42057-3_2

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-42057-3_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-42056-6

  • Online ISBN: 978-3-642-42057-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation