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A Robust Detection Algorithm for Infrared Maritime Small and Dim Targets

Infrared maritime target detection is the key technology of maritime target search systems. However, infrared images generally have the defects of low signal-to-noise ratio and low resolution. At the same time, the maritime environment is complicated and changeable. Under the interference of islands...

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Autores principales: Lu, Yuwei, Dong, Lili, Zhang, Tong, Xu, Wenhai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7070314/
https://www.ncbi.nlm.nih.gov/pubmed/32102474
http://dx.doi.org/10.3390/s20041237
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author Lu, Yuwei
Dong, Lili
Zhang, Tong
Xu, Wenhai
author_facet Lu, Yuwei
Dong, Lili
Zhang, Tong
Xu, Wenhai
author_sort Lu, Yuwei
collection PubMed
description Infrared maritime target detection is the key technology of maritime target search systems. However, infrared images generally have the defects of low signal-to-noise ratio and low resolution. At the same time, the maritime environment is complicated and changeable. Under the interference of islands, waves and other disturbances, the brightness of small dim targets is easily obscured, which makes them difficult to distinguish. This is difficult for traditional target detection algorithms to deal with. In order to solve these problems, through the analysis of infrared maritime images under a variety of sea conditions including small dim targets, this paper concludes that in infrared maritime images, small targets occupy very few pixels, often do not have any edge contour information, and the gray value and contrast values are very low. The background such as island and strong sea wave occupies a large number of pixels, with obvious texture features, and often has a high gray value. By deeply analyzing the difference between the target and the background, this paper proposes a detection algorithm (SRGM) for infrared small dim targets under different maritime background. Firstly, this algorithm proposes an efficient maritime background filter for the common background in the infrared maritime image. Firstly, the median filter based on the sensitive region selection is used to extract the image background accurately, and then the background is eliminated by image difference with the original image. In addition, this article analyzes the differences in gradient features between strong interference caused by the background and targets, proposes a small dim target extraction operator with two analysis factors that fit the target features perfectly and combines the adaptive threshold segmentation to realize the accurate extraction of the small dim target. The experimental results show that compared with the current popular small dim target detection algorithms, this paper has better performance for target detection in various maritime environments.
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spelling pubmed-70703142020-03-19 A Robust Detection Algorithm for Infrared Maritime Small and Dim Targets Lu, Yuwei Dong, Lili Zhang, Tong Xu, Wenhai Sensors (Basel) Article Infrared maritime target detection is the key technology of maritime target search systems. However, infrared images generally have the defects of low signal-to-noise ratio and low resolution. At the same time, the maritime environment is complicated and changeable. Under the interference of islands, waves and other disturbances, the brightness of small dim targets is easily obscured, which makes them difficult to distinguish. This is difficult for traditional target detection algorithms to deal with. In order to solve these problems, through the analysis of infrared maritime images under a variety of sea conditions including small dim targets, this paper concludes that in infrared maritime images, small targets occupy very few pixels, often do not have any edge contour information, and the gray value and contrast values are very low. The background such as island and strong sea wave occupies a large number of pixels, with obvious texture features, and often has a high gray value. By deeply analyzing the difference between the target and the background, this paper proposes a detection algorithm (SRGM) for infrared small dim targets under different maritime background. Firstly, this algorithm proposes an efficient maritime background filter for the common background in the infrared maritime image. Firstly, the median filter based on the sensitive region selection is used to extract the image background accurately, and then the background is eliminated by image difference with the original image. In addition, this article analyzes the differences in gradient features between strong interference caused by the background and targets, proposes a small dim target extraction operator with two analysis factors that fit the target features perfectly and combines the adaptive threshold segmentation to realize the accurate extraction of the small dim target. The experimental results show that compared with the current popular small dim target detection algorithms, this paper has better performance for target detection in various maritime environments. MDPI 2020-02-24 /pmc/articles/PMC7070314/ /pubmed/32102474 http://dx.doi.org/10.3390/s20041237 Text en © 2020 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
Lu, Yuwei
Dong, Lili
Zhang, Tong
Xu, Wenhai
A Robust Detection Algorithm for Infrared Maritime Small and Dim Targets
title A Robust Detection Algorithm for Infrared Maritime Small and Dim Targets
title_full A Robust Detection Algorithm for Infrared Maritime Small and Dim Targets
title_fullStr A Robust Detection Algorithm for Infrared Maritime Small and Dim Targets
title_full_unstemmed A Robust Detection Algorithm for Infrared Maritime Small and Dim Targets
title_short A Robust Detection Algorithm for Infrared Maritime Small and Dim Targets
title_sort robust detection algorithm for infrared maritime small and dim targets
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7070314/
https://www.ncbi.nlm.nih.gov/pubmed/32102474
http://dx.doi.org/10.3390/s20041237
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