Perceptual Fusion of Electronic Chart and Marine Radar Image

Electronic charts and marine radars are indispensable equipment in ship navigation systems, and the fusion display of these two parts ensures that the vessel can display dangerous moving targets and various obstacles on the sea. To reduce the noise interference caused by external factors and hardwar...

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Autores principales:	Chuang Zhang, Meihan Fang, Chunyu Yang, Renhai Yu, Tieshan Li
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	image denoising image fusion generative adversarial network electronic nautical charts radar image Naval architecture. Shipbuilding. Marine engineering VM1-989 Oceanography GC1-1581
Acceso en línea:	https://doaj.org/article/672ef8158ee64e8396fad2fd12573740
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id	oai:doaj.org-article:672ef8158ee64e8396fad2fd12573740
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spelling	oai:doaj.org-article:672ef8158ee64e8396fad2fd125737402021-11-25T18:04:40ZPerceptual Fusion of Electronic Chart and Marine Radar Image10.3390/jmse91112452077-1312https://doaj.org/article/672ef8158ee64e8396fad2fd125737402021-11-01T00:00:00Zhttps://www.mdpi.com/2077-1312/9/11/1245https://doaj.org/toc/2077-1312Electronic charts and marine radars are indispensable equipment in ship navigation systems, and the fusion display of these two parts ensures that the vessel can display dangerous moving targets and various obstacles on the sea. To reduce the noise interference caused by external factors and hardware, a novel radar image denoising algorithm using the concept of Generative Adversarial Network (GAN) using Wasserstein distance is proposed. GAN focuses on transferring the image noise distribution between strong and weak noise, while the perceptual loss approach is to suppress the noise by comparing the perceptual characteristics of the output after denoising. Afterwards, an image registration method based on image transformation is proposed to eliminate the imaging difference between the radar image and chart image, in which the visual attribute transfer approach is used to transform images. Finally, the sparse theory is used to process the high frequency and low frequency subband coefficients of the detection image obtained by the fast Fourier transform in parallel to realizing the image fusion. The results show that the fused contour has a high consistency, fast training speed and short registration time.Chuang ZhangMeihan FangChunyu YangRenhai YuTieshan LiMDPI AGarticleimage denoisingimage fusiongenerative adversarial networkelectronic nautical chartsradar imageNaval architecture. Shipbuilding. Marine engineeringVM1-989OceanographyGC1-1581ENJournal of Marine Science and Engineering, Vol 9, Iss 1245, p 1245 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	image denoising image fusion generative adversarial network electronic nautical charts radar image Naval architecture. Shipbuilding. Marine engineering VM1-989 Oceanography GC1-1581
spellingShingle	image denoising image fusion generative adversarial network electronic nautical charts radar image Naval architecture. Shipbuilding. Marine engineering VM1-989 Oceanography GC1-1581 Chuang Zhang Meihan Fang Chunyu Yang Renhai Yu Tieshan Li Perceptual Fusion of Electronic Chart and Marine Radar Image
description	Electronic charts and marine radars are indispensable equipment in ship navigation systems, and the fusion display of these two parts ensures that the vessel can display dangerous moving targets and various obstacles on the sea. To reduce the noise interference caused by external factors and hardware, a novel radar image denoising algorithm using the concept of Generative Adversarial Network (GAN) using Wasserstein distance is proposed. GAN focuses on transferring the image noise distribution between strong and weak noise, while the perceptual loss approach is to suppress the noise by comparing the perceptual characteristics of the output after denoising. Afterwards, an image registration method based on image transformation is proposed to eliminate the imaging difference between the radar image and chart image, in which the visual attribute transfer approach is used to transform images. Finally, the sparse theory is used to process the high frequency and low frequency subband coefficients of the detection image obtained by the fast Fourier transform in parallel to realizing the image fusion. The results show that the fused contour has a high consistency, fast training speed and short registration time.
format	article
author	Chuang Zhang Meihan Fang Chunyu Yang Renhai Yu Tieshan Li
author_facet	Chuang Zhang Meihan Fang Chunyu Yang Renhai Yu Tieshan Li
author_sort	Chuang Zhang
title	Perceptual Fusion of Electronic Chart and Marine Radar Image
title_short	Perceptual Fusion of Electronic Chart and Marine Radar Image
title_full	Perceptual Fusion of Electronic Chart and Marine Radar Image
title_fullStr	Perceptual Fusion of Electronic Chart and Marine Radar Image
title_full_unstemmed	Perceptual Fusion of Electronic Chart and Marine Radar Image
title_sort	perceptual fusion of electronic chart and marine radar image
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/672ef8158ee64e8396fad2fd12573740
work_keys_str_mv	AT chuangzhang perceptualfusionofelectronicchartandmarineradarimage AT meihanfang perceptualfusionofelectronicchartandmarineradarimage AT chunyuyang perceptualfusionofelectronicchartandmarineradarimage AT renhaiyu perceptualfusionofelectronicchartandmarineradarimage AT tieshanli perceptualfusionofelectronicchartandmarineradarimage
_version_	1718411683434594304

Perceptual Fusion of Electronic Chart and Marine Radar Image

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