A Fast Computation Method for IQA Metrics Based on their Typical Set

Vittoria Bruni, Domenico Vitulano

2014

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.

Paper Citation

in Harvard Style

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 - Volume 1: ICPRAM, ISBN 978-989-758-018-5, pages 199-206. DOI: 10.5220/0004820301990206

in Bibtex Style

@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 - Volume 1: ICPRAM,},
year={2014},
pages={199-206},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004820301990206},
isbn={978-989-758-018-5},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - A Fast Computation Method for IQA Metrics Based on their Typical Set
SN - 978-989-758-018-5
AU - Bruni V.
AU - Vitulano D.
PY - 2014
SP - 199
EP - 206
DO - 10.5220/0004820301990206