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Authors: Vittoria Bruni 1 and Domenico Vitulano 2

Affiliations: 1 University of Rome La Sapienza and Istituto per le Applicazioni del Calcolo, Italy ; 2 Istituto per le Applicazioni del Calcolo, Italy

Keyword(s): Information Theory, SSIM, Image Quality Assessment, Typical Set.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Image and Video Analysis ; Visual Attention and Image Saliency

Abstract: The paper presents a model for assessing image quality from a subset of pixels. It is based on the fact that human beings do not explore the whole image information for quantifying its degree of distortion. Hence, the vision process can be seen in agreement with the Asymptotic Equipartition Property. The latter assures the existence of a subset of sequences of image blocks able to describe the whole image source with a prefixed and small error. Specifically, the well known Structural SIMilarity index (SSIM) has been considered. Its entropy has been used for defining a method for the selection of those image pixels that enable SSIM estimation with enough precision. Experimental results show that the proposed selection method is able to reduce the number of operations required by SSIM of about 200 times, with an estimation error less than 8%.

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Paper citation in several formats:
Bruni, V. and Vitulano, D. (2016). An Entropy-based Model for a Fast Computation of SSIM. In Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2016) - Volume 4: VISAPP; ISBN 978-989-758-175-5; ISSN 2184-4321, SciTePress, pages 226-233. DOI: 10.5220/0005730002260233

@conference{visapp16,
author={Vittoria Bruni. and Domenico Vitulano.},
title={An Entropy-based Model for a Fast Computation of SSIM},
booktitle={Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2016) - Volume 4: VISAPP},
year={2016},
pages={226-233},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005730002260233},
isbn={978-989-758-175-5},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2016) - Volume 4: VISAPP
TI - An Entropy-based Model for a Fast Computation of SSIM
SN - 978-989-758-175-5
IS - 2184-4321
AU - Bruni, V.
AU - Vitulano, D.
PY - 2016
SP - 226
EP - 233
DO - 10.5220/0005730002260233
PB - SciTePress

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