Image quality assessment based on S-CIELAB model

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

Image quality assessment based on S-CIELAB model

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

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Publication Type:: Journal Article
Citation:: Signal, Image and Video Processing, 2011, 5 (3), pp. 283 - 290
Issue Date:: 2011-09-01

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Field	Value	Language
dc.contributor.author	He, L	en_US
dc.contributor.author	Gao, X	en_US
dc.contributor.author	Lu, W	en_US
dc.contributor.author	Li, X	en_US
dc.contributor.author	Tao, D https://orcid.org/0000-0001-7225-5449	en_US
dc.date.issued	2011-09-01	en_US
dc.identifier.citation	Signal, Image and Video Processing, 2011, 5 (3), pp. 283 - 290	en_US
dc.identifier.issn	1863-1703	en_US
dc.identifier.uri	http://hdl.handle.net/10453/15193
dc.description.abstract	This paper proposes a new image quality assessment framework which is based on color perceptual model. By analyzing the shortages of the existing image quality assessment methods and combining the color perceptual model, the general framework of color image quality assessment based on the S-CIELAB color space is presented. The S-CIELAB color model, a spatial extension of CIELAB, has an excellent performance for mimicking the perceptual processing of human color vision. This paper incorporates excellent color perceptual characteristics model with the geometrical distortion measurement to assess the image quality. First, the reference and distorted images are transformed into S-CIELAB color perceptual space, and the transformed images are evaluated by existing metric in three color perceptual channels. The fidelity factors of three channels are weighted to obtain the image quality. Experimental results achieved on LIVE database II shows that the proposed methods are in good consistency with human subjective assessment results. © 2011 Springer-Verlag London Limited.	en_US
dc.relation.ispartof	Signal, Image and Video Processing	en_US
dc.relation.isbasedon	10.1007/s11760-010-0200-x	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	Image quality assessment based on S-CIELAB model	en_US
dc.type	Journal Article
utslib.citation.volume	3	en_US
utslib.citation.volume	5	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
utslib.for	0906 Electrical and Electronic Engineering	en_US
dc.location.activity	Darwin, Australia
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.issue	3	en_US
pubs.publication-status	Published	en_US
pubs.volume	5	en_US

Abstract:

This paper proposes a new image quality assessment framework which is based on color perceptual model. By analyzing the shortages of the existing image quality assessment methods and combining the color perceptual model, the general framework of color image quality assessment based on the S-CIELAB color space is presented. The S-CIELAB color model, a spatial extension of CIELAB, has an excellent performance for mimicking the perceptual processing of human color vision. This paper incorporates excellent color perceptual characteristics model with the geometrical distortion measurement to assess the image quality. First, the reference and distorted images are transformed into S-CIELAB color perceptual space, and the transformed images are evaluated by existing metric in three color perceptual channels. The fidelity factors of three channels are weighted to obtain the image quality. Experimental results achieved on LIVE database II shows that the proposed methods are in good consistency with human subjective assessment results. © 2011 Springer-Verlag London Limited.

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http://hdl.handle.net/10453/15193