Universal no reference image quality assessment metrics based on local dependency

Gao, F; Gao, X; Tao, D; Li, X; He, L; Lu, W

Universal no reference image quality assessment metrics based on local dependency

Gao, F Gao, X Tao, D

Li, X He, L Lu, W

Permalink

Publication Type:: Conference Proceeding
Citation:: 1st Asian Conference on Pattern Recognition, ACPR 2011, 2011, pp. 298 - 302
Issue Date:: 2011-12-01

Closed Access

	Filename	Description	Size
	06166657.pdf	Published version	729.5 kB	Adobe PDF	View/Open

Copyright Clearance Process

Recently Added
In Progress
Closed Access

This item is closed access and not available.

Full metadata record

Field	Value	Language
dc.contributor.author	Gao, F	en_US
dc.contributor.author	Gao, X	en_US
dc.contributor.author	Tao, D https://orcid.org/0000-0001-7225-5449	en_US
dc.contributor.author	Li, X	en_US
dc.contributor.author	He, L	en_US
dc.contributor.author	Lu, W	en_US
dc.date.issued	2011-12-01	en_US
dc.identifier.citation	1st Asian Conference on Pattern Recognition, ACPR 2011, 2011, pp. 298 - 302	en_US
dc.identifier.isbn	9781457701221	en_US
dc.identifier.uri	http://hdl.handle.net/10453/119438
dc.description.abstract	No reference image quality assessment (NR-IQA) is to evaluate image quality blindly without the ground truth. Most of the emerging NR-IQA algorithms are only effective for some specific distortion. Universal metrics that can work for various categories of distortions have hardly been explored, and the algorithms available are not fully adequate in performance. In this paper, we study the local dependency (LD) characteristic of natural images, and propose two universal NR-IQA metrics: LD global scheme (LD-GS) and LD two-step scheme (LD-TS). We claim that the local dependency characteristic among wavelet coefficients is disturbed by various distortion processes, and the disturbances are strongly correlated to image qualities. Experimental results on LIVE database II demonstrate that both the proposed metrics are highly consistent with the human perception and outpace the state-of-the-art NR-IQA indexes and some full reference quality indicators for diverse distortions and across the entire database. © 2011 IEEE.	en_US
dc.relation.ispartof	1st Asian Conference on Pattern Recognition, ACPR 2011	en_US
dc.relation.isbasedon	10.1109/ACPR.2011.6166657	en_US
dc.title	Universal no reference image quality assessment metrics based on local dependency	en_US
dc.type	Conference Proceeding
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

No reference image quality assessment (NR-IQA) is to evaluate image quality blindly without the ground truth. Most of the emerging NR-IQA algorithms are only effective for some specific distortion. Universal metrics that can work for various categories of distortions have hardly been explored, and the algorithms available are not fully adequate in performance. In this paper, we study the local dependency (LD) characteristic of natural images, and propose two universal NR-IQA metrics: LD global scheme (LD-GS) and LD two-step scheme (LD-TS). We claim that the local dependency characteristic among wavelet coefficients is disturbed by various distortion processes, and the disturbances are strongly correlated to image qualities. Experimental results on LIVE database II demonstrate that both the proposed metrics are highly consistent with the human perception and outpace the state-of-the-art NR-IQA indexes and some full reference quality indicators for diverse distortions and across the entire database. © 2011 IEEE.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/119438