基于Takagi-Sugeno-Kang模糊模型的三维图像质量评价

2014 IEEE 12th International Symposium on Intelligent Systems and Informatics (SISY) Pub Date : 2014-10-16 DOI:10.1109/SISY.2014.6923607

D. Dordevic, D. Kukolj, P. Callet

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引用次数: 0

摘要

本文利用模糊逻辑估计器即Takagi-Sugeno-Kang模糊模型，分析了无参考和全参考两类客观图像质量评价测度对三维图像感知质量的影响。基于两种模型输入的选择，本文进行了对比分析。根据所选择的输入客观质量度量与相应的差分平均意见分数(DMOS)的映射标准集，对无参考和全参考Takagi-Sugeno-Kang模型的所有参数进行优化。

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3D image quality assessment using Takagi-Sugeno-Kang fuzzy modele

This paper analyzes and presents impact of two types of the objective image quality assessment measures, no-reference and full-reference measures, on perception quality of 3D image using fuzzy logic estimator namely the Takagi-Sugeno-Kang fuzzy model. Based on the choice of two types of model's inputs, a comparative analysis is performed in this paper. All parameters of the no-reference and full-reference Takagi-Sugeno-Kang models are optimized in accordance to the selected sets mapping criteria of the input objective quality measures to the corresponding Differential Mean Opinion Scores (DMOS).

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来源期刊

2014 IEEE 12th International Symposium on Intelligent Systems and Informatics (SISY)

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