Skip to main content
SpringerLink
Log in

Comparison of Super-Resolution Methods for HD-Video Endoscopy

  • Chapter
  • First Online:
Book cover Bildverarbeitung für die Medizin 2014

Part of the book series: Informatik aktuell ((INFORMAT))

Abstract

The main question we try to answer in this work is whether it is feasible to employ super-resolution (SR) algorithms to increase the spatial resolution of endoscopic high-definition (HD) images in order to reveal new details which may have got lost due to the limited endoscope magnification of the HD endoscope used (e.g. mucosal structures).

For this purpose we compare the quality achieved of different SR methods. This is done on standard test images as well as on images obtained from endoscopic video frames. We also investigate whether compression artifacts have a noticeable effect on the SR results.

We show that, due to several limitations in case of endoscopic videos, we are not consistently able to achieve a higher visual quality when using SR algorithms instead of bicubic interpolation.

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 79.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 84.99
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. Tischendorf JJW, Gross S, Winograd R, et al. Computer-aided classification of colorectal polyps based on vascular patterns: a pilot study. Endoscopy. 2010;42(3):203–7.

    Article  Google Scholar 

  2. Duda K, Zieli´nski T, Duplaga M. Computationally simple super-resolution algorithm for video from endoscopic capsule. Proc ICSES. 2008; p. 197–200.

    Google Scholar 

  3. List P, Joch A, Lainema J, et al. Adaptive Deblocking Filter. IEEE Trans Circuits Syst Video Technol. 2003;13(7):614–9.

    Article  Google Scholar 

  4. Liu C. Beyond pixels: exploring new representations and applications for motion analysis [dissertation]. Massachusetts Institute of Technology; 2009.

    Google Scholar 

  5. Elad M. A fast super-resolution reconstruction algorithm for pure translational motion and common space-invariant blur. IEEE Trans Image Process. 2001;10(8):1187–93.

    Article  MATH  MathSciNet  Google Scholar 

  6. Farsiu S, Robinson D, Elad M, et al. Advances and challenges in super-resolution. Int J Imaging Syst Technol. 2004;14(2):47–57.

    Article  Google Scholar 

  7. Irani M, Peleg S. Improving resolution by image registration. Comp Vis Graph Image Process. 1991 Apr;53(3):231–9.

    Google Scholar 

  8. Zomet A, Rav-Acha A, Peleg S. Robust super-resolution. Proc IEEE. 2001;1:645–50.

    Google Scholar 

  9. Mittal A, Moorthy AK, Bovik AC. No-reference image quality assessment in the spatial domain. IEEE Trans Image Process. 2012;21(12):4695–708.

    Article  MathSciNet  Google Scholar 

  10. Gabarda S, Crist´obal G. Blind image quality assessment through anisotropy. J Opt Soc Am A. 2007;24(12):B42–51.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department for Internal Medicine, St. Elisabeth Hospital, Vienna, Österreich

    M. Häfner

  2. Department of Computer Sciences, University of Salzburg, Salzburg, Austria

    M. Liedlgruber & A. Uhl

Authors
  1. M. Häfner
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. M. Liedlgruber
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. A. Uhl
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to M. Häfner .

Editor information

Editors and Affiliations

  1. Institut für Medizinische Informatik, Uniklinik RWTH Aachen, Aachen, Germany

    Thomas Martin Deserno

  2. Institut für Medizinische Informatik, Universität zu Lübeck, Lübeck, Germany

    Heinz Handels

  3. Abteilung für Medizinische und Biologische Informatik, Deutsches Krebsforschungszentrum, Heidelberg, Germany

    Hans-Peter Meinzer

  4. Institut für Medizinische Informatik, Charité – Universitätsmedizin Berlin, Berlin, Berlin, Germany

    Thomas Tolxdorff

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Häfner, M., Liedlgruber, M., Uhl, A. (2014). Comparison of Super-Resolution Methods for HD-Video Endoscopy. In: Deserno, T., Handels, H., Meinzer, HP., Tolxdorff, T. (eds) Bildverarbeitung für die Medizin 2014. Informatik aktuell. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54111-7_19

Download citation

Publish with us

Policies and ethics

Search

Navigation