Progressive Depth Learning for Single Image Dehazing Article Swipe
Yudong Liang
,
Bin Wang
,
Jiaying Liu
,
Deyu Li
,
Sanping Zhou
,
Wenqi Ren
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2102.10514
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2102.10514
The formulation of the hazy image is mainly dominated by the reflected lights and ambient airlight. Existing dehazing methods often ignore the depth cues and fail in distant areas where heavier haze disturbs the visibility. However, we note that the guidance of the depth information for transmission estimation could remedy the decreased visibility as distances increase. In turn, the good transmission estimation could facilitate the depth estimation for hazy images. In this paper, a deep end-to-end model that iteratively estimates image depths and transmission maps is proposed to perform an effective depth prediction for hazy images and improve the dehazing performance with the guidance of depth information. The image depth and transmission map are progressively refined to better restore the dehazed image. Our approach benefits from explicitly modeling the inner relationship of image depth and transmission map, which is especially effective for distant hazy areas. Extensive results on the benchmarks demonstrate that our proposed network performs favorably against the state-of-the-art dehazing methods in terms of depth estimation and haze removal.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2102.10514
- https://arxiv.org/pdf/2102.10514
- OA Status
- green
- Cited By
- 3
- References
- 19
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3129661164
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3129661164Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2102.10514Digital Object Identifier
- Title
-
Progressive Depth Learning for Single Image DehazingWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-02-21Full publication date if available
- Authors
-
Yudong Liang, Bin Wang, Jiaying Liu, Deyu Li, Sanping Zhou, Wenqi RenList of authors in order
- Landing page
-
https://arxiv.org/abs/2102.10514Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2102.10514Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/2102.10514Direct OA link when available
- Concepts
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Visibility, Computer science, Haze, Transmission (telecommunications), Artificial intelligence, Depth map, Computer vision, Image (mathematics), Estimation, Geography, Telecommunications, Meteorology, Economics, ManagementTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
3Total citation count in OpenAlex
- Citations by year (recent)
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2022: 3Per-year citation counts (last 5 years)
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19Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.estimation | 47, 61, 66, 166 |
| abstract_inverted_index.explicitly | 126 |
| abstract_inverted_index.facilitate | 63 |
| abstract_inverted_index.prediction | 92 |
| abstract_inverted_index.visibility | 52 |
| abstract_inverted_index.demonstrate | 150 |
| abstract_inverted_index.formulation | 1 |
| abstract_inverted_index.information | 44 |
| abstract_inverted_index.iteratively | 78 |
| abstract_inverted_index.performance | 100 |
| abstract_inverted_index.visibility. | 34 |
| abstract_inverted_index.information. | 106 |
| abstract_inverted_index.relationship | 130 |
| abstract_inverted_index.transmission | 46, 60, 83, 111, 135 |
| abstract_inverted_index.progressively | 114 |
| abstract_inverted_index.state-of-the-art | 159 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 6 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/11 |
| sustainable_development_goals[0].score | 0.4099999964237213 |
| sustainable_development_goals[0].display_name | Sustainable cities and communities |
| citation_normalized_percentile |