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Proceedings Paper

Image quality assessment using Takagi-Sugeno-Kang fuzzy model
Author(s): Dragana Đorđević; Dragan Kukolj; Peter Schelkens
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Paper Abstract

The main aim of the paper is to present a non-linear image quality assessment model based on a fuzzy logic estimator, namely the Takagi-Sugeno-Kang fuzzy model. This image quality assessment model uses a clustered space of input objective metrics. Main advantages of the introduced quality model are simplicity and understandably of its fuzzy rules. As reference model the polynomial 3 rd order model was chosen. The parameters of the Takagi-Sugeno-Kang fuzzy model are optimized in accordance to the mapping criteria of the selected set of input objective quality measures to the Mean Opinion Score (MOS) scale.

Paper Details

Date Published: 4 March 2015
PDF: 8 pages
Proc. SPIE 9443, Sixth International Conference on Graphic and Image Processing (ICGIP 2014), 94430Z (4 March 2015); doi: 10.1117/12.2178767
Show Author Affiliations
Dragana Đorđević, RT-RK Institute for Computer Based Systems (Serbia)
Dragan Kukolj, Univ. of Novi Sad (Serbia)
Peter Schelkens, iMinds (Belgium)
Vrije Univ. Brussel (Belgium)

Published in SPIE Proceedings Vol. 9443:
Sixth International Conference on Graphic and Image Processing (ICGIP 2014)
Yulin Wang; Xudong Jiang; David Zhang, Editor(s)

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