JOURNAL ARTICLE

Image quality assessment using Takagi-Sugeno-Kang fuzzy model

Dragana ĐorđevićDragan KukoljPeter Schelkens

Year: 2015 Journal:   Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE Vol: 9443 Pages: 94430Z-94430Z   Publisher: SPIE

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.

Keywords:
Fuzzy logic Computer science Quality (philosophy) Data mining Estimator Set (abstract data type) Fuzzy set Mathematics Artificial intelligence Machine learning Statistics

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0.21
FWCI (Field Weighted Citation Impact)
12
Refs
0.59
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Citation History

Topics

Image and Video Quality Assessment
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Image Fusion Techniques
Physical Sciences →  Engineering →  Media Technology
Image and Signal Denoising Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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