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Iterative Refinement of Transmission Map for Stereo Image Defogging Using a Dual Camera Sensor

Recently, the stereo imaging-based image enhancement approach has attracted increasing attention in the field of video analysis. This paper presents a dual camera-based stereo image defogging algorithm. Optical flow is first estimated from the stereo foggy image pair, and the initial disparity map i...

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Detalles Bibliográficos
Autores principales: Kim, Heegwang, Park, Jinho, Park, Hasil, Paik, Joonki
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5751095/
https://www.ncbi.nlm.nih.gov/pubmed/29232826
http://dx.doi.org/10.3390/s17122861
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author Kim, Heegwang
Park, Jinho
Park, Hasil
Paik, Joonki
author_facet Kim, Heegwang
Park, Jinho
Park, Hasil
Paik, Joonki
author_sort Kim, Heegwang
collection PubMed
description Recently, the stereo imaging-based image enhancement approach has attracted increasing attention in the field of video analysis. This paper presents a dual camera-based stereo image defogging algorithm. Optical flow is first estimated from the stereo foggy image pair, and the initial disparity map is generated from the estimated optical flow. Next, an initial transmission map is generated using the initial disparity map. Atmospheric light is then estimated using the color line theory. The defogged result is finally reconstructed using the estimated transmission map and atmospheric light. The proposed method can refine the transmission map iteratively. Experimental results show that the proposed method can successfully remove fog without color distortion. The proposed method can be used as a pre-processing step for an outdoor video analysis system and a high-end smartphone with a dual camera system.
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spelling pubmed-57510952018-01-10 Iterative Refinement of Transmission Map for Stereo Image Defogging Using a Dual Camera Sensor Kim, Heegwang Park, Jinho Park, Hasil Paik, Joonki Sensors (Basel) Article Recently, the stereo imaging-based image enhancement approach has attracted increasing attention in the field of video analysis. This paper presents a dual camera-based stereo image defogging algorithm. Optical flow is first estimated from the stereo foggy image pair, and the initial disparity map is generated from the estimated optical flow. Next, an initial transmission map is generated using the initial disparity map. Atmospheric light is then estimated using the color line theory. The defogged result is finally reconstructed using the estimated transmission map and atmospheric light. The proposed method can refine the transmission map iteratively. Experimental results show that the proposed method can successfully remove fog without color distortion. The proposed method can be used as a pre-processing step for an outdoor video analysis system and a high-end smartphone with a dual camera system. MDPI 2017-12-09 /pmc/articles/PMC5751095/ /pubmed/29232826 http://dx.doi.org/10.3390/s17122861 Text en © 2017 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Kim, Heegwang
Park, Jinho
Park, Hasil
Paik, Joonki
Iterative Refinement of Transmission Map for Stereo Image Defogging Using a Dual Camera Sensor
title Iterative Refinement of Transmission Map for Stereo Image Defogging Using a Dual Camera Sensor
title_full Iterative Refinement of Transmission Map for Stereo Image Defogging Using a Dual Camera Sensor
title_fullStr Iterative Refinement of Transmission Map for Stereo Image Defogging Using a Dual Camera Sensor
title_full_unstemmed Iterative Refinement of Transmission Map for Stereo Image Defogging Using a Dual Camera Sensor
title_short Iterative Refinement of Transmission Map for Stereo Image Defogging Using a Dual Camera Sensor
title_sort iterative refinement of transmission map for stereo image defogging using a dual camera sensor
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5751095/
https://www.ncbi.nlm.nih.gov/pubmed/29232826
http://dx.doi.org/10.3390/s17122861
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