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Endoscopic video defogging using luminance blending

Endoscopic video sequences provide surgeons with direct surgical field or visualisation on anatomical targets in the patient during robotic surgery. Unfortunately, these video images are unavoidably hazy or foggy to prevent surgeons from clear surgical vision due to typical surgical operations such...

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Detalles Bibliográficos
Autores principales: Luo, Xiongbiao, Yang, Fan, Zeng, Hui-Qing, Du, Yan-Ping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Institution of Engineering and Technology 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6952256/
https://www.ncbi.nlm.nih.gov/pubmed/32038872
http://dx.doi.org/10.1049/htl.2019.0095
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author Luo, Xiongbiao
Yang, Fan
Zeng, Hui-Qing
Du, Yan-Ping
author_facet Luo, Xiongbiao
Yang, Fan
Zeng, Hui-Qing
Du, Yan-Ping
author_sort Luo, Xiongbiao
collection PubMed
description Endoscopic video sequences provide surgeons with direct surgical field or visualisation on anatomical targets in the patient during robotic surgery. Unfortunately, these video images are unavoidably hazy or foggy to prevent surgeons from clear surgical vision due to typical surgical operations such as ablation and cauterisation during surgery. This Letter aims at removing fog or smoke on endoscopic video sequences to enhance and maintain a direct and clear visualisation of the operating field during robotic surgery. The authors propose a new luminance blending framework that integrates contrast enhancement with visibility restoration for foggy endoscopic video processing. The proposed method was validated on clinical endoscopic videos that were collected from robotic surgery. The experimental results demonstrate that their method provides a promising means to effectively remove fog or smoke on endoscopic video images. In particular, the visual quality of defogged endoscopic images was improved from 0.5088 to 0.6475.
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spelling pubmed-69522562020-02-07 Endoscopic video defogging using luminance blending Luo, Xiongbiao Yang, Fan Zeng, Hui-Qing Du, Yan-Ping Healthc Technol Lett Special Issue: Papers from the 13th Workshop on Augmented Environments for Computer Assisted Interventions Endoscopic video sequences provide surgeons with direct surgical field or visualisation on anatomical targets in the patient during robotic surgery. Unfortunately, these video images are unavoidably hazy or foggy to prevent surgeons from clear surgical vision due to typical surgical operations such as ablation and cauterisation during surgery. This Letter aims at removing fog or smoke on endoscopic video sequences to enhance and maintain a direct and clear visualisation of the operating field during robotic surgery. The authors propose a new luminance blending framework that integrates contrast enhancement with visibility restoration for foggy endoscopic video processing. The proposed method was validated on clinical endoscopic videos that were collected from robotic surgery. The experimental results demonstrate that their method provides a promising means to effectively remove fog or smoke on endoscopic video images. In particular, the visual quality of defogged endoscopic images was improved from 0.5088 to 0.6475. The Institution of Engineering and Technology 2019-12-06 /pmc/articles/PMC6952256/ /pubmed/32038872 http://dx.doi.org/10.1049/htl.2019.0095 Text en http://creativecommons.org/licenses/by/3.0/ This is an open access article published by the IET under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)
spellingShingle Special Issue: Papers from the 13th Workshop on Augmented Environments for Computer Assisted Interventions
Luo, Xiongbiao
Yang, Fan
Zeng, Hui-Qing
Du, Yan-Ping
Endoscopic video defogging using luminance blending
title Endoscopic video defogging using luminance blending
title_full Endoscopic video defogging using luminance blending
title_fullStr Endoscopic video defogging using luminance blending
title_full_unstemmed Endoscopic video defogging using luminance blending
title_short Endoscopic video defogging using luminance blending
title_sort endoscopic video defogging using luminance blending
topic Special Issue: Papers from the 13th Workshop on Augmented Environments for Computer Assisted Interventions
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6952256/
https://www.ncbi.nlm.nih.gov/pubmed/32038872
http://dx.doi.org/10.1049/htl.2019.0095
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