Single Image Dehazing via Saliency Weighted Multi-exposure Fusion

LI Hongyun; SHI Yun; GAO Yin

doi:10.11999/JEIT200931

Volume 44 Issue 1

Jan. 2022

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Article Navigation > Journal of Electronics & Information Technology > 2022 > 44(1): 261-270

LI Hongyun, SHI Yun, GAO Yin. Single Image Dehazing via Saliency Weighted Multi-exposure Fusion[J]. Journal of Electronics & Information Technology, 2022, 44(1): 261-270. doi: 10.11999/JEIT200931

Citation:

LI Hongyun, SHI Yun, GAO Yin. Single Image Dehazing via Saliency Weighted Multi-exposure Fusion[J]. Journal of Electronics & Information Technology, 2022, 44(1): 261-270. doi: 10.11999/JEIT200931

LI Hongyun, SHI Yun, GAO Yin. Single Image Dehazing via Saliency Weighted Multi-exposure Fusion[J]. Journal of Electronics & Information Technology, 2022, 44(1): 261-270. doi: 10.11999/JEIT200931

Citation:

LI Hongyun, SHI Yun, GAO Yin. Single Image Dehazing via Saliency Weighted Multi-exposure Fusion[J]. Journal of Electronics & Information Technology, 2022, 44(1): 261-270. doi: 10.11999/JEIT200931

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Single Image Dehazing via Saliency Weighted Multi-exposure Fusion

doi: 10.11999/JEIT200931

LI Hongyun¹,
SHI Yun¹,
GAO Yin^{2
,
,}

1.
Quanzhou Vocational and Technical University, Jinjiang 362200, China
2.
Quanzhou Institute of Equipment Manufacturing, Jinjiang 362200, China

Funds: The National Natural Science Foundation of China (62001452), The Fujian Province Young band Middle-aged Teacher Education Research Project(JAT191675), The Science and Technology Program of Quanzhou (2020C054, 2019C009R)

Received Date: 2020-10-30
Rev Recd Date: 2021-04-20

Available Online: 2021-08-18

Publish Date: 2022-01-10

Abstract

Abstract

Previous techniques are not sufficient enough to deal with dehazing problems by using various hand-crafted priors and appear image hue and brightness distortion. In this paper, a saliency weighted multi-exposure fusion is proposed for single image dehazing. To produce several images with different exposures, a novel segmentation method is exploited to capture the range of global atmospheric light approximately, and a new Kirsh high-order difference filtering method is employed to optimize the transmission map. A saliency weighted multi-exposure fusion method is constructed to improve the dehazing quality. Extensive experimental results on both subjective and objective evaluation demonstrate that the proposed algorithm performs favorably against the state-of-the-art algorithms.
- Image dehazing,
- Adaptive boundary constraint,
- High order difference filtering,
- Saliency weighted multi-exposure fusion

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References(35)

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