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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Institution of Engineering and Technology
2019
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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. |
format | Online Article Text |
id | pubmed-6952256 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | The Institution of Engineering and Technology |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT luoxiongbiao endoscopicvideodefoggingusingluminanceblending AT yangfan endoscopicvideodefoggingusingluminanceblending AT zenghuiqing endoscopicvideodefoggingusingluminanceblending AT duyanping endoscopicvideodefoggingusingluminanceblending |