Paper
17 January 2005 A perceptual quality metric for color-interpolated images
Author Affiliations +
Proceedings Volume 5668, Image Quality and System Performance II; (2005) https://doi.org/10.1117/12.587624
Event: Electronic Imaging 2005, 2005, San Jose, California, United States
Abstract
An objective image quality metric can be used to compare the output of different image processing algorithms, but objective measures are not always well correlated with subjective image quality assessment; the latter implies the use of human observers, thus objective methods able to emulate the Human Visual System (HVS) better than the classical measures are preferred. In this paper a full reference objective metric, based on perceptual criteria and oriented to demosaiced images is proposed. The basic idea is to model the main artifacts produced by the interpolation process, taking into account the HVS sensibility to the typical aliasing and the zipper defects. The proposed technique has been compared to the DE94 CIELAB metric. Furthermore, two subjective tests have been performed; one relative to the color aliasing artifact and one to the zipper effect. The experimental results highlight that the quality scores obtained by the proposed measures have a similar trend to the DE94 CIELAB metric. Moreover, subjective tests are in accordance with the obtained results. This technique is useful to evaluate the quality of the interpolation techniques implemented in the image processing pipeline of different digital still cameras.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ivana Guarneri, Mirko Guarnera, Angelo Bosco, and Gaetano Santoro "A perceptual quality metric for color-interpolated images", Proc. SPIE 5668, Image Quality and System Performance II, (17 January 2005); https://doi.org/10.1117/12.587624
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Cited by 3 scholarly publications.
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KEYWORDS
Image quality

Lithium

Image processing

Quality measurement

Error analysis

Video

Digital image processing

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