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Quality Evaluation of Image Dehazing Methods Using Synthetic Hazy Images
Xiongkuo Min1,2; Guangtao Zhai1; Ke Gu3; Yucheng Zhu1; Jiantao Zhou4,5; Guodong Guo6; Xiaokang Yang1; Xinping Guan7; Wenjun Zhang1
Source PublicationIEEE Transactions on Multimedia

To enhance the visibility and usability of images captured in hazy conditions, many image dehazing algorithms (DHAs) have been proposed. With so many image DHAs, there is a need to evaluate and compare these DHAs. Due to the lack of the reference haze-free images, DHAs are generally evaluated qualitatively using real hazy images. But it is possible to perform quantitative evaluation using synthetic hazy images since the reference haze-free images are available and full-reference (FR) image quality assessment (IQA) measures can be utilized. In this paper, we follow this strategy and study DHA evaluation using synthetic hazy images systematically. We first build a synthetic haze removing quality (SHRQ) database. It consists of two subsets: regular and aerial image subsets, which include 360 and 240 dehazed images created from 45 and 30 synthetic hazy images using 8 DHAs, respectively. Since aerial imaging is an important application area of dehazing, we create an aerial image subset specifically. We then carry out subjective quality evaluation study on these two subsets. We observe that taking DHA evaluation as an exact FR IQA process is questionable, and the state-of-the-art FR IQA measures are not effective for DHA evaluation. Thus, we propose a DHA quality evaluation method by integrating some dehazing-relevant features, including image structure recovering, color rendition, and over-enhancement of low-contrast areas. The proposed method works for both types of images, but we further improve it for aerial images by incorporating its specific characteristics. Experimental results on two subsets of the SHRQ database validate the effectiveness of the proposed measures.

KeywordDehazing Algorithm Evaluation Image Dehazing Quality Assessment Regular/aerial Image Synthetic Haze
URLView the original
Indexed BySCIE
WOS Research AreaComputer Science ; Telecommunications
WOS SubjectComputer Science, Information systemsComputer Science, Software Engineeringtelecommunications
WOS IDWOS:000483015200013
Scopus ID2-s2.0-85063761434
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Cited Times [WOS]:62   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionFaculty of Science and Technology
Corresponding AuthorGuangtao Zhai
Affiliation1.Institute of Image Communication and Network Engineering,Shanghai Jiao Tong University,Shanghai,200240,China
2.Department of Computer and Information Science,University of Macau,999078,Macao
3.Beijing Key Laboratory of Computational Intelligence and Intelligent System,Faculty of Information Technology,Beijing University of Technology,Beijing,100124,China
4.Department of Computer and Information Science,Faculty of Science and Technology,
5.State Key Laboratory of Internet of Things for Smart City,University of Macau,999078,Macao
6.Institute of Deep Learning,National Engineering Laboratory for Deep Learning Technology and Application,Baidu Research,Beijing,100193,China
7.Department of Automation,Shanghai Jiao Tong University,Shanghai,200240,China
First Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Xiongkuo Min,Guangtao Zhai,Ke Gu,et al. Quality Evaluation of Image Dehazing Methods Using Synthetic Hazy Images[J]. IEEE Transactions on Multimedia,2019,21(9):2319-2333.
APA Xiongkuo Min,Guangtao Zhai,Ke Gu,Yucheng Zhu,Jiantao Zhou,Guodong Guo,Xiaokang Yang,Xinping Guan,&Wenjun Zhang.(2019).Quality Evaluation of Image Dehazing Methods Using Synthetic Hazy Images.IEEE Transactions on Multimedia,21(9),2319-2333.
MLA Xiongkuo Min,et al."Quality Evaluation of Image Dehazing Methods Using Synthetic Hazy Images".IEEE Transactions on Multimedia 21.9(2019):2319-2333.
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