Framework for Applying Full Reference Digital Image Quality Measures to Printed Images

  • Authors:
  • Tuomas Eerola;Joni-Kristian Kämäräinen;Lasse Lensu;Heikki Kälviäinen

  • Affiliations:
  • Machine Vision and Pattern Recognition Research Group (MVPR) MVPR/Computational Vision Group, Kouvola Department of Information Technology, Lappeenranta University of Technology (LUT), Finland;Machine Vision and Pattern Recognition Research Group (MVPR) MVPR/Computational Vision Group, Kouvola Department of Information Technology, Lappeenranta University of Technology (LUT), Finland;Machine Vision and Pattern Recognition Research Group (MVPR) MVPR/Computational Vision Group, Kouvola Department of Information Technology, Lappeenranta University of Technology (LUT), Finland;Machine Vision and Pattern Recognition Research Group (MVPR) MVPR/Computational Vision Group, Kouvola Department of Information Technology, Lappeenranta University of Technology (LUT), Finland

  • Venue:
  • SCIA '09 Proceedings of the 16th Scandinavian Conference on Image Analysis
  • Year:
  • 2009

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Abstract

Measuring visual quality of printed media is important as printed products play an essential role in every day life, and for many "vision applications", printed products still dominate the market (e.g., newspapers). Measuring visual quality, especially the quality of images when the original is known (full-reference), has been an active research topic in image processing. During the course of work, several good measures have been proposed and shown to correspond with human (subjective) evaluations. Adapting these approaches to measuring visual quality of printed media has been considered only rarely and is not straightforward. In this work, the aim is to reduce the gap by presenting a complete framework starting from the original digital image and its hard-copy reproduction to a scanned digital sample which is compared to the original reference image by using existing quality measures. The proposed framework is justified by experiments where the measures are compared to a subjective evaluation performed using the printed hard copies.