IDE: Image Dehazing and Exposure Using an Enhanced Atmospheric Scattering Model.

Ju, M; Ding, C; Ren, W; Yang, Y; Zhang, D; Guo, YJ

IDE: Image Dehazing and Exposure Using an Enhanced Atmospheric Scattering Model.

Ju, M

Ding, C

Ren, W Yang, Y Zhang, D Guo, YJ

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Publisher:: Institute of Electrical and Electronics Engineers (IEEE)
Publication Type:: Journal Article
Citation:: IEEE transactions on image processing : a publication of the IEEE Signal Processing Society, 2021, 30, pp. 2180-2192
Issue Date:: 2021-01-26

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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	Ren, W
dc.contributor.author	Yang, Y
dc.contributor.author	Zhang, D
dc.contributor.author	Guo, YJ
dc.date.accessioned	2021-02-17T04:51:30Z
dc.date.available	2021-02-17T04:51:30Z
dc.date.issued	2021-01-26
dc.identifier.citation	IEEE transactions on image processing : a publication of the IEEE Signal Processing Society, 2021, 30, pp. 2180-2192
dc.identifier.issn	1057-7149
dc.identifier.issn	1941-0042
dc.identifier.uri	http://hdl.handle.net/10453/146170
dc.description.abstract	Atmospheric scattering model (ASM) is one of the most widely used model to describe the imaging processing of hazy images. However, we found that ASM has an intrinsic limitation which leads to a dim effect in the recovered results. In this paper, by introducing a new parameter, i.e., light absorption coefficient, into ASM, an enhanced ASM (EASM) is attained, which can address the dim effect and better model outdoor hazy scenes. Relying on this EASM, a simple yet effective gray-world-assumption-based technique called IDE is then developed to enhance the visibility of hazy images. Experimental results show that IDE eliminates the dim effect and exhibits excellent dehazing performance. It is worth mentioning that IDE does not require any training process or extra information related to scene depth, which makes it very fast and robust. Moreover, the global stretch strategy used in IDE can effectively avoid some undesirable effects in recovery results, e.g., over-enhancement, over-saturation, and mist residue, etc. Comparison between the proposed IDE and other state-of-the-art techniques reveals the superiority of IDE in terms of both dehazing quality and efficiency over all the comparable techniques.
dc.format	Print-Electronic
dc.language	eng
dc.publisher	Institute of Electrical and Electronics Engineers (IEEE)
dc.relation.ispartof	IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
dc.relation.isbasedon	10.1109/tip.2021.3050643
dc.rights	info:eu-repo/semantics/openAccess
dc.rights	© 2021 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	0801 Artificial Intelligence and Image Processing, 0906 Electrical and Electronic Engineering, 1702 Cognitive Sciences
dc.subject.classification	Artificial Intelligence & Image Processing
dc.title	IDE: Image Dehazing and Exposure Using an Enhanced Atmospheric Scattering Model.
dc.type	Journal Article
utslib.citation.volume	30
utslib.location.activity	United States
utslib.for	0801 Artificial Intelligence and Image Processing
utslib.for	0906 Electrical and Electronic Engineering
utslib.for	1702 Cognitive Sciences
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney
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
utslib.copyright.status	open_access	*
dc.date.updated	2021-02-17T04:51:21Z
pubs.publication-status	Published
pubs.volume	30

Abstract:

Atmospheric scattering model (ASM) is one of the most widely used model to describe the imaging processing of hazy images. However, we found that ASM has an intrinsic limitation which leads to a dim effect in the recovered results. In this paper, by introducing a new parameter, i.e., light absorption coefficient, into ASM, an enhanced ASM (EASM) is attained, which can address the dim effect and better model outdoor hazy scenes. Relying on this EASM, a simple yet effective gray-world-assumption-based technique called IDE is then developed to enhance the visibility of hazy images. Experimental results show that IDE eliminates the dim effect and exhibits excellent dehazing performance. It is worth mentioning that IDE does not require any training process or extra information related to scene depth, which makes it very fast and robust. Moreover, the global stretch strategy used in IDE can effectively avoid some undesirable effects in recovery results, e.g., over-enhancement, over-saturation, and mist residue, etc. Comparison between the proposed IDE and other state-of-the-art techniques reveals the superiority of IDE in terms of both dehazing quality and efficiency over all the comparable techniques.

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http://hdl.handle.net/10453/146170