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Infrared Sensation-Based Salient Targets Enhancement Methods in Low-Visibility Scenes

Thermal imaging is an important technology in low-visibility environments, and due to the blurred edges and low contrast of infrared images, enhancement processing is of vital importance. However, to some extent, the existing enhancement algorithms based on pixel-level information ignore the salient...

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Autores principales: Tan, Hongjun, Ou, Dongxiu, Zhang, Lei, Shen, Guochen, Li, Xinghua, Ji, Yuqing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9370932/
https://www.ncbi.nlm.nih.gov/pubmed/35957389
http://dx.doi.org/10.3390/s22155835
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author Tan, Hongjun
Ou, Dongxiu
Zhang, Lei
Shen, Guochen
Li, Xinghua
Ji, Yuqing
author_facet Tan, Hongjun
Ou, Dongxiu
Zhang, Lei
Shen, Guochen
Li, Xinghua
Ji, Yuqing
author_sort Tan, Hongjun
collection PubMed
description Thermal imaging is an important technology in low-visibility environments, and due to the blurred edges and low contrast of infrared images, enhancement processing is of vital importance. However, to some extent, the existing enhancement algorithms based on pixel-level information ignore the salient feature of targets, the temperature which effectively separates the targets by their color. Therefore, based on the temperature and pixel features of infrared images, first, a threshold denoising model based on wavelet transformation with bilateral filtering (WTBF) was proposed. Second, our group proposed a salient components enhancement method based on a multi-scale retinex algorithm combined with frequency-tuned salient region extraction (MSRFT). Third, the image contrast and noise distribution were improved by using salient features of orientation, color, and illuminance of night or snow targets. Finally, the accuracy of the bounding box of enhanced images was tested by the pre-trained and improved object detector. The results show that the improved method can reach an accuracy of 90% of snow targets, and the average precision of car and people categories improved in four low-visibility scenes, which demonstrates the high accuracy and adaptability of the proposed methods of great significance for target detection, trajectory tracking, and danger warning of automobile driving.
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spelling pubmed-93709322022-08-12 Infrared Sensation-Based Salient Targets Enhancement Methods in Low-Visibility Scenes Tan, Hongjun Ou, Dongxiu Zhang, Lei Shen, Guochen Li, Xinghua Ji, Yuqing Sensors (Basel) Article Thermal imaging is an important technology in low-visibility environments, and due to the blurred edges and low contrast of infrared images, enhancement processing is of vital importance. However, to some extent, the existing enhancement algorithms based on pixel-level information ignore the salient feature of targets, the temperature which effectively separates the targets by their color. Therefore, based on the temperature and pixel features of infrared images, first, a threshold denoising model based on wavelet transformation with bilateral filtering (WTBF) was proposed. Second, our group proposed a salient components enhancement method based on a multi-scale retinex algorithm combined with frequency-tuned salient region extraction (MSRFT). Third, the image contrast and noise distribution were improved by using salient features of orientation, color, and illuminance of night or snow targets. Finally, the accuracy of the bounding box of enhanced images was tested by the pre-trained and improved object detector. The results show that the improved method can reach an accuracy of 90% of snow targets, and the average precision of car and people categories improved in four low-visibility scenes, which demonstrates the high accuracy and adaptability of the proposed methods of great significance for target detection, trajectory tracking, and danger warning of automobile driving. MDPI 2022-08-04 /pmc/articles/PMC9370932/ /pubmed/35957389 http://dx.doi.org/10.3390/s22155835 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
Tan, Hongjun
Ou, Dongxiu
Zhang, Lei
Shen, Guochen
Li, Xinghua
Ji, Yuqing
Infrared Sensation-Based Salient Targets Enhancement Methods in Low-Visibility Scenes
title Infrared Sensation-Based Salient Targets Enhancement Methods in Low-Visibility Scenes
title_full Infrared Sensation-Based Salient Targets Enhancement Methods in Low-Visibility Scenes
title_fullStr Infrared Sensation-Based Salient Targets Enhancement Methods in Low-Visibility Scenes
title_full_unstemmed Infrared Sensation-Based Salient Targets Enhancement Methods in Low-Visibility Scenes
title_short Infrared Sensation-Based Salient Targets Enhancement Methods in Low-Visibility Scenes
title_sort infrared sensation-based salient targets enhancement methods in low-visibility scenes
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9370932/
https://www.ncbi.nlm.nih.gov/pubmed/35957389
http://dx.doi.org/10.3390/s22155835
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