Performance Evaluation of Super-Resolution Reconstruction Methods on Real-World Data

  • AWM van EekerenEmail author
  • K Schutte
  • OR Oudegeest
  • LJ van Vliet
Open Access
Research Article
Part of the following topical collections:
  1. Super-Resolution Enhancement of Digital Video


The performance of a super-resolution (SR) reconstruction method on real-world data is not easy to measure, especially as a ground-truth (GT) is often not available. In this paper, a quantitative performance measure is used, based on triangle orientation discrimination (TOD). The TOD measure, simulating a real-observer task, is capable of determining the performance of a specific SR reconstruction method under varying conditions of the input data. It is shown that the performance of an SR reconstruction method on real-world data can be predicted accurately by measuring its performance on simulated data. This prediction of the performance on real-world data enables the optimization of the complete chain of a vision system; from camera setup and SR reconstruction up to image detection/recognition/identification. Furthermore, different SR reconstruction methods are compared to show that the TOD method is a useful tool to select a specific SR reconstruction method according to the imaging conditions (camera's fill-factor, optical point-spread-function (PSF), signal-to-noise ratio (SNR)).


Information Technology Input Data Performance Evaluation Vision System Simulated Data 


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Copyright information

© A.W. M. van Eekeren et al. 2007

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 2.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Authors and Affiliations

  • AWM van Eekeren
    • 1
    Email author
  • K Schutte
    • 1
  • OR Oudegeest
    • 2
  • LJ van Vliet
    • 2
  1. 1.Electro-Optics Group, TNO DefenceSecurity and SafetyThe HagueThe Netherlands
  2. 2.Quantitative Imaging Group, Department of Imaging Science and Technology, Faculty of Applied SciencesDelft University of TechnologyDelftThe Netherlands

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