Reduced-reference IQA in contourlet domain

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

Reduced-reference IQA in contourlet domain

Tao, D

Li, X Lu, W Gao, X

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Publication Type:: Journal Article
Citation:: IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 2009, 39 (6), pp. 1623 - 1627
Issue Date:: 2009-05-21

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Field	Value	Language
dc.contributor.author	Tao, D https://orcid.org/0000-0001-7225-5449	en_US
dc.contributor.author	Li, X	en_US
dc.contributor.author	Lu, W	en_US
dc.contributor.author	Gao, X	en_US
dc.date.issued	2009-05-21	en_US
dc.identifier.citation	IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 2009, 39 (6), pp. 1623 - 1627	en_US
dc.identifier.issn	1083-4419	en_US
dc.identifier.uri	http://hdl.handle.net/10453/15071
dc.description.abstract	The human visual system (HVS) provides a suitable cue for image quality assessment (IQA). In this paper, we develop a novel reduced-reference (RR) IQA scheme by incorporating the merits from the contourlet transform, contrast sensitivity function (CSF), and Weber's law of just noticeable difference (JND). In this scheme, the contourlet transform is utilized to decompose images and then extract features to mimic the multichannel structure of HVS. CSF is applied to weight coefficients obtained by the contourlet transform to simulate the appearance of images to observers by taking into account many of the nonlinearities inherent in HVS. JND is finally introduced to produce a noticeable variation in sensory experience. Thorough empirical studies are carried out upon the Laboratory for Image and Video Engineering database against the subjective mean opinion score and demonstrate that the proposed framework has good consistency with subjective perception values and the objective assessment results can well reflect the visual quality of images. © 2009 IEEE.	en_US
dc.relation.ispartof	IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics	en_US
dc.relation.isbasedon	10.1109/TSMCB.2009.2021951	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.subject.mesh	Humans	en_US
dc.subject.mesh	Image Processing, Computer-Assisted	en_US
dc.subject.mesh	Pattern Recognition, Automated	en_US
dc.subject.mesh	Vision, Ocular	en_US
dc.title	Reduced-reference IQA in contourlet domain	en_US
dc.type	Journal Article
utslib.citation.volume	6	en_US
utslib.citation.volume	39	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
utslib.for	0102 Applied Mathematics	en_US
utslib.for	0906 Electrical and Electronic Engineering	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.issue	6	en_US
pubs.publication-status	Published	en_US
pubs.volume	39	en_US

Abstract:

The human visual system (HVS) provides a suitable cue for image quality assessment (IQA). In this paper, we develop a novel reduced-reference (RR) IQA scheme by incorporating the merits from the contourlet transform, contrast sensitivity function (CSF), and Weber's law of just noticeable difference (JND). In this scheme, the contourlet transform is utilized to decompose images and then extract features to mimic the multichannel structure of HVS. CSF is applied to weight coefficients obtained by the contourlet transform to simulate the appearance of images to observers by taking into account many of the nonlinearities inherent in HVS. JND is finally introduced to produce a noticeable variation in sensory experience. Thorough empirical studies are carried out upon the Laboratory for Image and Video Engineering database against the subjective mean opinion score and demonstrate that the proposed framework has good consistency with subjective perception values and the objective assessment results can well reflect the visual quality of images. © 2009 IEEE.

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http://hdl.handle.net/10453/15071