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Adapting a Dehazing System to Haze Conditions by Piece-Wisely Linearizing a Depth Estimator

Haze is the most frequently encountered weather condition on the road, and it accounts for a considerable number of car crashes occurring every year. Accordingly, image dehazing has garnered strong interest in recent decades. However, although various algorithms have been developed, a robust dehazin...

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Autores principales: Ngo, Dat, Lee, Seungmin, Kang, Ui-Jean, Ngo, Tri Minh, Lee, Gi-Dong, Kang, Bongsoon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8915013/
https://www.ncbi.nlm.nih.gov/pubmed/35271107
http://dx.doi.org/10.3390/s22051957
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author Ngo, Dat
Lee, Seungmin
Kang, Ui-Jean
Ngo, Tri Minh
Lee, Gi-Dong
Kang, Bongsoon
author_facet Ngo, Dat
Lee, Seungmin
Kang, Ui-Jean
Ngo, Tri Minh
Lee, Gi-Dong
Kang, Bongsoon
author_sort Ngo, Dat
collection PubMed
description Haze is the most frequently encountered weather condition on the road, and it accounts for a considerable number of car crashes occurring every year. Accordingly, image dehazing has garnered strong interest in recent decades. However, although various algorithms have been developed, a robust dehazing method that can operate reliably in different haze conditions is still in great demand. Therefore, this paper presents a method to adapt a dehazing system to various haze conditions. Under this approach, the proposed method discriminates haze conditions based on the haze density estimate. The discrimination result is then leveraged to form a piece-wise linear weight to modify the depth estimator. Consequently, the proposed method can effectively handle arbitrary input images regardless of their haze condition. This paper also presents a corresponding real-time hardware implementation to facilitate the integration into existing embedded systems. Finally, a comparative assessment against benchmark designs demonstrates the efficacy of the proposed dehazing method and its hardware counterpart.
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spelling pubmed-89150132022-03-12 Adapting a Dehazing System to Haze Conditions by Piece-Wisely Linearizing a Depth Estimator Ngo, Dat Lee, Seungmin Kang, Ui-Jean Ngo, Tri Minh Lee, Gi-Dong Kang, Bongsoon Sensors (Basel) Article Haze is the most frequently encountered weather condition on the road, and it accounts for a considerable number of car crashes occurring every year. Accordingly, image dehazing has garnered strong interest in recent decades. However, although various algorithms have been developed, a robust dehazing method that can operate reliably in different haze conditions is still in great demand. Therefore, this paper presents a method to adapt a dehazing system to various haze conditions. Under this approach, the proposed method discriminates haze conditions based on the haze density estimate. The discrimination result is then leveraged to form a piece-wise linear weight to modify the depth estimator. Consequently, the proposed method can effectively handle arbitrary input images regardless of their haze condition. This paper also presents a corresponding real-time hardware implementation to facilitate the integration into existing embedded systems. Finally, a comparative assessment against benchmark designs demonstrates the efficacy of the proposed dehazing method and its hardware counterpart. MDPI 2022-03-02 /pmc/articles/PMC8915013/ /pubmed/35271107 http://dx.doi.org/10.3390/s22051957 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Ngo, Dat
Lee, Seungmin
Kang, Ui-Jean
Ngo, Tri Minh
Lee, Gi-Dong
Kang, Bongsoon
Adapting a Dehazing System to Haze Conditions by Piece-Wisely Linearizing a Depth Estimator
title Adapting a Dehazing System to Haze Conditions by Piece-Wisely Linearizing a Depth Estimator
title_full Adapting a Dehazing System to Haze Conditions by Piece-Wisely Linearizing a Depth Estimator
title_fullStr Adapting a Dehazing System to Haze Conditions by Piece-Wisely Linearizing a Depth Estimator
title_full_unstemmed Adapting a Dehazing System to Haze Conditions by Piece-Wisely Linearizing a Depth Estimator
title_short Adapting a Dehazing System to Haze Conditions by Piece-Wisely Linearizing a Depth Estimator
title_sort adapting a dehazing system to haze conditions by piece-wisely linearizing a depth estimator
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8915013/
https://www.ncbi.nlm.nih.gov/pubmed/35271107
http://dx.doi.org/10.3390/s22051957
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