http://www.cnr.it/ontology/cnr/individuo/prodotto/ID291498
A fast computation method for IQA metrics based on their typical set (Contributo in atti di convegno)
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- Label
- A fast computation method for IQA metrics based on their typical set (Contributo in atti di convegno) (literal)
- Anno
- 2014-01-01T00:00:00+01:00 (literal)
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- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Bruni V.; Vitulano D. (literal)
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- Pagina fine
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
- http://www.scopus.com/inward/record.url?eid=2-s2.0-84902356988&partnerID=q2rCbXpz (literal)
- Note
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- Dept. of SBAI, Faculty of Engineering, Univ. of Rome Sapienza, Via A. Scarpa 16, 00161 Rome, Italy; Istituto per Le Applicazioni del Calcolo M. Picone, C.N.R., Via dei Taurini 19, 00185 Rome, Italy (literal)
- Titolo
- A fast computation method for IQA metrics based on their typical set (literal)
- 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. Copyright © 2014 SCITEPRESS. (literal)
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