Image Quality Assessment Using Takagi-Sugeno-Kang Fuzzy Model

Dragana Đorđević; Dragan Kukolj; Peter Schelkens

Image Quality Assessment Using Takagi-Sugeno-Kang Fuzzy Model

Dragana Đorđević
, Dragan Kukolj
, Peter Schelkens

Electronics and Informatics

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 3rd 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.

Original language	English
Title of host publication	3rd International Conference on Image, Vision and Computing (ICIVC)
Publisher	International Association of Computer Science and Information Technology (IACSIT)
Number of pages	8
Publication status	Published - 2014
Event	3rd International Conference on Image, Vision and Computing, ICIVC 2014 - Paris, France Duration: 17 Sept 2014 → 18 Sept 2014

Conference

Conference	3rd International Conference on Image, Vision and Computing, ICIVC 2014
Country/Territory	France
City	Paris
Period	17/09/14 → 18/09/14

Keywords

objective image quality assessment
fuzzy logic
Takagi-Sugeno-Kang fuzzy model

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Persistent link

SRP11: Strategic Research Programme: Processing of large scale multi-dimensional, multi-spectral, multi-sensorial and distributed data (M³D²)
Schelkens, P. (Administrative Promotor), Deligiannis, N. (Co-Promotor), Jansen, B. (Co-Promotor), Kuijk, M. (Co-Promotor), Munteanu, A. (Co-Promotor), Sahli, H. (Co-Promotor), Steenhaut, K. (Co-Promotor), Stiens, J. (Co-Promotor), Schelkens, P. (Administrative Promotor), Cornelis, J. P. (Co-Promotor), Kuijk, M. (Co-Promotor), Munteanu, A. (Co-Promotor), Sahli, H. (Co-Promotor), Stiens, J. (Co-Promotor) & Vounckx, R. (Co-Promotor)
1/11/12 → 31/12/23
Project: Fundamental

Cite this

@inproceedings{a2e4dd5decaf46f5abcc77544b926620,

title = "Image Quality Assessment Using Takagi-Sugeno-Kang Fuzzy Model",

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 3rd 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 = "objective image quality assessment, fuzzy logic, Takagi-Sugeno-Kang fuzzy model",

author = "Dragana {\D}or{\d}evi{\'c} and Dragan Kukolj and Peter Schelkens",

year = "2014",

language = "English",

booktitle = "3rd International Conference on Image, Vision and Computing (ICIVC)",

publisher = "International Association of Computer Science and Information Technology (IACSIT)",

note = "3rd International Conference on Image, Vision and Computing, ICIVC 2014 ; Conference date: 17-09-2014 Through 18-09-2014",

}

TY - GEN

T1 - Image Quality Assessment Using Takagi-Sugeno-Kang Fuzzy Model

AU - Đorđević, Dragana

AU - Kukolj, Dragan

AU - Schelkens, Peter

PY - 2014

Y1 - 2014

N2 - 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 3rd 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.

AB - 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 3rd 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.

KW - objective image quality assessment

KW - fuzzy logic

KW - Takagi-Sugeno-Kang fuzzy model

M3 - Conference paper

BT - 3rd International Conference on Image, Vision and Computing (ICIVC)

PB - International Association of Computer Science and Information Technology (IACSIT)

T2 - 3rd International Conference on Image, Vision and Computing, ICIVC 2014

Y2 - 17 September 2014 through 18 September 2014

ER -

Image Quality Assessment Using Takagi-Sugeno-Kang Fuzzy Model

Abstract

Conference

Keywords

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Projects

SRP11: Strategic Research Programme: Processing of large scale multi-dimensional, multi-spectral, multi-sensorial and distributed data (M³D²)

Cite this