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Authors: Vittoria Bruni 1 and Domenico Vitulano 2

Affiliations: 1 Faculty of Engineering, Univ. of Rome ”Sapienza” and Istituto per le Applicazioni del Calcolo ”M. Picone” - C.N.R., Italy ; 2 Istituto per le Applicazioni del Calcolo ”M. Picone” - C.N.R., Italy

Keyword(s): Information Theory, SSIM, Asymptotic Equipartition Property, Image Quality Assessment.

Related Ontology Subjects/Areas/Topics: Applications ; Model Selection ; Pattern Recognition ; Perception ; Theory and Methods

Abstract: This paper deals with the typical set of an image quality assessment (IQA) measure. In particular, it focuses on the well known and widely used Structural SIMilarity index (SSIM). In agreement with Information Theory, the visual distortion typical set is composed of the least amount of information necessary to estimate the quality of the distorted image. General criteria for an effective and fruitful computation of the set will be given. As it will be shown, the typical set allows to increase IQA efficiency by considerably speeding up its computation, thanks to the reduced number of image blocks used for the evaluation of the considered IQA metric.

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Paper citation in several formats:
Bruni, V. and Vitulano, D. (2014). A Fast Computation Method for IQA Metrics Based on their Typical Set. In Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-758-018-5; ISSN 2184-4313, SciTePress, pages 199-206. DOI: 10.5220/0004820301990206

@conference{icpram14,
author={Vittoria Bruni. and Domenico Vitulano.},
title={A Fast Computation Method for IQA Metrics Based on their Typical Set},
booktitle={Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - ICPRAM},
year={2014},
pages={199-206},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004820301990206},
isbn={978-989-758-018-5},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - A Fast Computation Method for IQA Metrics Based on their Typical Set
SN - 978-989-758-018-5
IS - 2184-4313
AU - Bruni, V.
AU - Vitulano, D.
PY - 2014
SP - 199
EP - 206
DO - 10.5220/0004820301990206
PB - SciTePress