Nonparametric Quality Assessment Of Natural Images

Redzuan , Abdul Manap (2016) Nonparametric Quality Assessment Of Natural Images. IEEE Multimedia, 23. pp. 22-30. ISSN 1070-986X

Text 2016 IEEE Multimedia - NPNO BIQA.pdf - Published Version Download (482kB)

Abstract

In this article,the authors explore an alternative way to perform no-reference image quality assessment (NR-IQA). Following a feature extraction stage in which spatial domain statistics are utilized as features,a two-stage nonparametric NR-IQA framework is proposed.This approach requires no training phase,and it enables prediction of the image distortion type as well as local regions' quality, which is not available in most current algorithms. Experimental results on IQA databases show that the proposed framework achieves high correlation to human perception of image quality and delivers competitive performance to state-of-the-art NR-IQA algorithms.

Item Type:	Article
Subjects:	Q Science > Q Science (General) Q Science > QA Mathematics
Divisions:	Faculty of Electronics and Computer Engineering > Department of Telecommunication Engineering
Depositing User:	Mohd. Nazir Taib
Date Deposited:	28 May 2018 00:54
Last Modified:	12 Jul 2021 03:28
URI:	http://eprints.utem.edu.my/id/eprint/20967
Statistic Details:	View Download Statistic

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