Image quality assessment using Takagi-Sugeno-Kang fuzzy model

Dragana Đorđević; Dragan Kukolj; Peter Schelkens

doi:10.1117/12.2178767

4 March 2015 Image quality assessment using Takagi-Sugeno-Kang fuzzy model

Dragana Đorđević, Dragan Kukolj, Peter Schelkens

Proceedings Volume 9443, Sixth International Conference on Graphic and Image Processing (ICGIP 2014); 94430Z (2015) https://doi.org/10.1117/12.2178767
Event: Sixth International Conference on Graphic and Image Processing (ICGIP 2014), 2014, Beijing, China

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.

Citation Download Citation

Dragana Đorđević, Dragan Kukolj, and Peter Schelkens "Image quality assessment using Takagi-Sugeno-Kang fuzzy model", Proc. SPIE 9443, Sixth International Conference on Graphic and Image Processing (ICGIP 2014), 94430Z (4 March 2015); https://doi.org/10.1117/12.2178767

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