A Flexible Region of Interest Extraction Algorithm with Adaptive Threshold for 3-D Synthetic Aperture Radar Images

Most of the existing image segmentation methods have a strong anti-noise ability but are susceptible to the interference in the background, so they are not suitable for 3-D synthetic aperture radar (SAR) image target extraction. Region of interest (ROI) extraction can improve the anti-interference a...

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Autores principales:	Liang Li, Xiaoling Zhang, Bokun Tian, Chen Wang, Liming Pu, Jun Shi, Shunjun Wei
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	synthetic aperture radar (SAR) image segmentation target extraction 3-D saliency detection Science Q
Acceso en línea:	https://doaj.org/article/9bf5464f99e6439ea42b9f08d9a61d99
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spelling	oai:doaj.org-article:9bf5464f99e6439ea42b9f08d9a61d992021-11-11T18:53:35ZA Flexible Region of Interest Extraction Algorithm with Adaptive Threshold for 3-D Synthetic Aperture Radar Images10.3390/rs132143082072-4292https://doaj.org/article/9bf5464f99e6439ea42b9f08d9a61d992021-10-01T00:00:00Zhttps://www.mdpi.com/2072-4292/13/21/4308https://doaj.org/toc/2072-4292Most of the existing image segmentation methods have a strong anti-noise ability but are susceptible to the interference in the background, so they are not suitable for 3-D synthetic aperture radar (SAR) image target extraction. Region of interest (ROI) extraction can improve the anti-interference ability of the image segmentation methods. However, the existing ROI extraction method uses the same threshold to process all the images in the data set. This threshold is not optimal for each image. Designed for 3-D SAR image target extraction, we propose an ROI extraction algorithm with adaptive threshold (REAT) to enhance the anti-interference ability of the existing image segmentation methods. The required thresholds in the proposed algorithm are adaptively obtained by the mapping of the image features. Moreover, the proposed algorithm can easily be applied to existing image segmentation methods. The experiments demonstrate that the proposed algorithm significantly enhances the anti-interference ability and computational efficiency of the image segmentation methods. Compared with the existing ROI extraction algorithm, the proposed algorithm improves the dice similarity coefficient by 6.4%.Liang LiXiaoling ZhangBokun TianChen WangLiming PuJun ShiShunjun WeiMDPI AGarticlesynthetic aperture radar (SAR)image segmentationtarget extraction3-Dsaliency detectionScienceQENRemote Sensing, Vol 13, Iss 4308, p 4308 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	synthetic aperture radar (SAR) image segmentation target extraction 3-D saliency detection Science Q
spellingShingle	synthetic aperture radar (SAR) image segmentation target extraction 3-D saliency detection Science Q Liang Li Xiaoling Zhang Bokun Tian Chen Wang Liming Pu Jun Shi Shunjun Wei A Flexible Region of Interest Extraction Algorithm with Adaptive Threshold for 3-D Synthetic Aperture Radar Images
description	Most of the existing image segmentation methods have a strong anti-noise ability but are susceptible to the interference in the background, so they are not suitable for 3-D synthetic aperture radar (SAR) image target extraction. Region of interest (ROI) extraction can improve the anti-interference ability of the image segmentation methods. However, the existing ROI extraction method uses the same threshold to process all the images in the data set. This threshold is not optimal for each image. Designed for 3-D SAR image target extraction, we propose an ROI extraction algorithm with adaptive threshold (REAT) to enhance the anti-interference ability of the existing image segmentation methods. The required thresholds in the proposed algorithm are adaptively obtained by the mapping of the image features. Moreover, the proposed algorithm can easily be applied to existing image segmentation methods. The experiments demonstrate that the proposed algorithm significantly enhances the anti-interference ability and computational efficiency of the image segmentation methods. Compared with the existing ROI extraction algorithm, the proposed algorithm improves the dice similarity coefficient by 6.4%.
format	article
author	Liang Li Xiaoling Zhang Bokun Tian Chen Wang Liming Pu Jun Shi Shunjun Wei
author_facet	Liang Li Xiaoling Zhang Bokun Tian Chen Wang Liming Pu Jun Shi Shunjun Wei
author_sort	Liang Li
title	A Flexible Region of Interest Extraction Algorithm with Adaptive Threshold for 3-D Synthetic Aperture Radar Images
title_short	A Flexible Region of Interest Extraction Algorithm with Adaptive Threshold for 3-D Synthetic Aperture Radar Images
title_full	A Flexible Region of Interest Extraction Algorithm with Adaptive Threshold for 3-D Synthetic Aperture Radar Images
title_fullStr	A Flexible Region of Interest Extraction Algorithm with Adaptive Threshold for 3-D Synthetic Aperture Radar Images
title_full_unstemmed	A Flexible Region of Interest Extraction Algorithm with Adaptive Threshold for 3-D Synthetic Aperture Radar Images
title_sort	flexible region of interest extraction algorithm with adaptive threshold for 3-d synthetic aperture radar images
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/9bf5464f99e6439ea42b9f08d9a61d99
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A Flexible Region of Interest Extraction Algorithm with Adaptive Threshold for 3-D Synthetic Aperture Radar Images

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