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Proceedings Paper

Reduced-reference quality metrics for measuring the image quality of digitally printed natural images
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Paper Abstract

The goal of the study was to develop a method for quality computation of digitally printed images. We wanted to use only the attributes which have a meaning for subjective visual quality experience of digitally printed images. Based on the subjective data and our assessments the attributes for quality calculation were sharpness, graininess and color contrast. The proposed graininess metric divides the fine detail image into blocks and used the low energy blocks for graininess calculation. The proposed color contrast metric computes the contrast of dominant colors using the coarse scale image. The proposed sharpness metric divides the coarse scale image into blocks and uses the high energy blocks for sharpness calculation. The reduced reference features of sharpness and graininess metrics are the numbers of high or low energy blocks. The reduced reference features of the color contrast metric are the directions of the dominant colors in reference image. The overall image quality was calculated by combining the values. The performance of proposed application specific image quality metric was high compared to the state of the art reduced reference applicationindependent image quality metric. Linear correlation coefficients between subjective and predicted MOS were 0.88 for electrophotography and 0.98 for ink-jet printed samples, for a sample set of 21 prints for electrophotography and for inkjet, subjectively evaluated by 28 observers.

Paper Details

Date Published: 18 January 2010
PDF: 12 pages
Proc. SPIE 7529, Image Quality and System Performance VII, 75290I (18 January 2010); doi: 10.1117/12.838883
Show Author Affiliations
Mikko Nuutinen, Helsinki Univ. of Technology (Finland)
Raisa Halonen, Helsinki Univ. of Technology (Finland)
Tuomas Leisti, Univ. of Helsinki (Finland)
Pirkko Oittinen, Helsinki Univ. of Technology (Finland)


Published in SPIE Proceedings Vol. 7529:
Image Quality and System Performance VII
Susan P. Farnand; Frans Gaykema, Editor(s)

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