VROHI: Visibility Recovery for Outdoor Hazy Image in Scattering Media

Ju, M; Ding, C; Guo, YJ

VROHI: Visibility Recovery for Outdoor Hazy Image in Scattering Media

Ju, M

Ding, C

Guo, YJ

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Publisher:: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Publication Type:: Journal Article
Citation:: IEEE Photonics Journal, 2020, 12, (6)
Issue Date:: 2020-12-01

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Field	Value	Language
dc.contributor.author	Ju, M https://orcid.org/0000-0003-4378-3781
dc.contributor.author	Ding, C https://orcid.org/0000-0002-2629-1657
dc.contributor.author	Guo, YJ
dc.date.accessioned	2021-02-01T05:57:29Z
dc.date.available	2021-02-01T05:57:29Z
dc.date.issued	2020-12-01
dc.identifier.citation	IEEE Photonics Journal, 2020, 12, (6)
dc.identifier.issn	1943-0655
dc.identifier.issn	1943-0655
dc.identifier.uri	http://hdl.handle.net/10453/145694
dc.description.abstract	© 2009-2012 IEEE. Additive haze model (AHM), due to its high simplicity, has a potential to increase the efficiency of the restoration procedure of images degraded by scattering media. However, AHM is designed for hazy remote sensing data and is not suitable to be used on outdoor images. In this paper, according to the low-frequency feature (LFC) of haze, AHM is modified via gamma correction technique to make it suitable for modeling outdoor images. Benefitting from the modified AHM (MAHM), a simple yet effective method called VROHI is proposed to enhance the visibility of an outdoor hazy image. In specific, a low complexity LFC extraction method is designed by utilizing characteristic of the discrete cosine transform. Subsequently, by constructing the linear function of unknown parameters and imposing the saturation prior on MAHM, the image dehazing problem can be derived into a global optimization function. Experiments reveal that the proposed VROHI is superior to the other state-of-the-art techniques in terms of both the processing efficiency and recovery quality.
dc.language	English
dc.publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.relation.ispartof	IEEE Photonics Journal
dc.relation.isbasedon	10.1109/JPHOT.2020.3036873
dc.rights	info:eu-repo/semantics/openAccess
dc.rights	© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.	en_US
dc.subject	0205 Optical Physics, 0906 Electrical and Electronic Engineering, 1005 Communications Technologies
dc.title	VROHI: Visibility Recovery for Outdoor Hazy Image in Scattering Media
dc.type	Journal Article
utslib.citation.volume	12
utslib.for	0205 Optical Physics
utslib.for	0906 Electrical and Electronic Engineering
utslib.for	1005 Communications Technologies
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney
utslib.copyright.status	open_access	*
pubs.consider-herdc	false
dc.date.updated	2021-02-01T05:57:19Z
pubs.issue	6
pubs.publication-status	Published
pubs.volume	12
utslib.citation.issue	6

Abstract:

© 2009-2012 IEEE. Additive haze model (AHM), due to its high simplicity, has a potential to increase the efficiency of the restoration procedure of images degraded by scattering media. However, AHM is designed for hazy remote sensing data and is not suitable to be used on outdoor images. In this paper, according to the low-frequency feature (LFC) of haze, AHM is modified via gamma correction technique to make it suitable for modeling outdoor images. Benefitting from the modified AHM (MAHM), a simple yet effective method called VROHI is proposed to enhance the visibility of an outdoor hazy image. In specific, a low complexity LFC extraction method is designed by utilizing characteristic of the discrete cosine transform. Subsequently, by constructing the linear function of unknown parameters and imposing the saturation prior on MAHM, the image dehazing problem can be derived into a global optimization function. Experiments reveal that the proposed VROHI is superior to the other state-of-the-art techniques in terms of both the processing efficiency and recovery quality.

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http://hdl.handle.net/10453/145694