The Method of UAV Image Object Detection under Foggy Weather by Style Transfer

Under the bad weather conditions such as foggy or rainy weather, the details of UAV images are seriously lost. Consequently, directly detecting without dehazing may lead to object missing and wrong inspection. Although the method of dehazing firstly and then detecting can significantly improve the d...

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Autor principal:	Yin Xuping, Zhong Ping, Xue Wei, Xiao Zixuan, Li Guang
Formato:	article
Lenguaje:	ZH
Publicado:	Editorial Office of Aero Weaponry 2021
Materias:	\|uav image\|fog image\|style transfer\|target detection\|image classification Motor vehicles. Aeronautics. Astronautics TL1-4050
Acceso en línea:	https://doaj.org/article/9a3cbd6f07514b0693f3812bac8bcdfd
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id	oai:doaj.org-article:9a3cbd6f07514b0693f3812bac8bcdfd
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spelling	oai:doaj.org-article:9a3cbd6f07514b0693f3812bac8bcdfd2021-11-30T00:13:41ZThe Method of UAV Image Object Detection under Foggy Weather by Style Transfer1673-504810.12132/ISSN.1673-5048.2020.0212https://doaj.org/article/9a3cbd6f07514b0693f3812bac8bcdfd2021-06-01T00:00:00Zhttps://www.aeroweaponry.avic.com/fileup/1673-5048/PDF/2020.00212.pdfhttps://doaj.org/toc/1673-5048Under the bad weather conditions such as foggy or rainy weather, the details of UAV images are seriously lost. Consequently, directly detecting without dehazing may lead to object missing and wrong inspection. Although the method of dehazing firstly and then detecting can significantly improve the detection performance of UAV images under misty weather conditions, it can not solve the problem that object detection model relies too much on the texture and surface information of the targets in the image which are used to classify, and thus leads to a poor detection performance on heavy fog images. In response to this problem, a method to detect after style transfer instead of haze removal is proposed to accomplish object detection of the UAV images under dense fog weather conditions. The method can change the style of the image while keep the content in image unchanged, making the object detection model transform from learning the object texture and surface information to learning the object contour, which is a more difficult task. The experiment is carried out on the UAV dataset Visdrone2019. Firstly, the UAV images are divided into fog-free, mist and dense fog images by using the differences in gradient features, dark channel features and wavelet features of fog images. Secondly, the processing methods of dehazing and style transfer are adopted respectively according to the concentration of fog. The experimental results show that the proposed method can further reduce the impact of light and noise, and can significantly improve the object detection performance of UAV dense fog images. Moreover, combining with the method of dehazing firstly and then detecting, the proposed method can adaptively complete the object detection task of UAV fog images.Yin Xuping, Zhong Ping, Xue Wei, Xiao Zixuan, Li GuangEditorial Office of Aero Weaponryarticle\|uav image\|fog image\|style transfer\|target detection\|image classificationMotor vehicles. Aeronautics. AstronauticsTL1-4050ZHHangkong bingqi, Vol 28, Iss 3, Pp 22-30 (2021)
institution	DOAJ
collection	DOAJ
language	ZH
topic	\|uav image\|fog image\|style transfer\|target detection\|image classification Motor vehicles. Aeronautics. Astronautics TL1-4050
spellingShingle	\|uav image\|fog image\|style transfer\|target detection\|image classification Motor vehicles. Aeronautics. Astronautics TL1-4050 Yin Xuping, Zhong Ping, Xue Wei, Xiao Zixuan, Li Guang The Method of UAV Image Object Detection under Foggy Weather by Style Transfer
description	Under the bad weather conditions such as foggy or rainy weather, the details of UAV images are seriously lost. Consequently, directly detecting without dehazing may lead to object missing and wrong inspection. Although the method of dehazing firstly and then detecting can significantly improve the detection performance of UAV images under misty weather conditions, it can not solve the problem that object detection model relies too much on the texture and surface information of the targets in the image which are used to classify, and thus leads to a poor detection performance on heavy fog images. In response to this problem, a method to detect after style transfer instead of haze removal is proposed to accomplish object detection of the UAV images under dense fog weather conditions. The method can change the style of the image while keep the content in image unchanged, making the object detection model transform from learning the object texture and surface information to learning the object contour, which is a more difficult task. The experiment is carried out on the UAV dataset Visdrone2019. Firstly, the UAV images are divided into fog-free, mist and dense fog images by using the differences in gradient features, dark channel features and wavelet features of fog images. Secondly, the processing methods of dehazing and style transfer are adopted respectively according to the concentration of fog. The experimental results show that the proposed method can further reduce the impact of light and noise, and can significantly improve the object detection performance of UAV dense fog images. Moreover, combining with the method of dehazing firstly and then detecting, the proposed method can adaptively complete the object detection task of UAV fog images.
format	article
author	Yin Xuping, Zhong Ping, Xue Wei, Xiao Zixuan, Li Guang
author_facet	Yin Xuping, Zhong Ping, Xue Wei, Xiao Zixuan, Li Guang
author_sort	Yin Xuping, Zhong Ping, Xue Wei, Xiao Zixuan, Li Guang
title	The Method of UAV Image Object Detection under Foggy Weather by Style Transfer
title_short	The Method of UAV Image Object Detection under Foggy Weather by Style Transfer
title_full	The Method of UAV Image Object Detection under Foggy Weather by Style Transfer
title_fullStr	The Method of UAV Image Object Detection under Foggy Weather by Style Transfer
title_full_unstemmed	The Method of UAV Image Object Detection under Foggy Weather by Style Transfer
title_sort	method of uav image object detection under foggy weather by style transfer
publisher	Editorial Office of Aero Weaponry
publishDate	2021
url	https://doaj.org/article/9a3cbd6f07514b0693f3812bac8bcdfd
work_keys_str_mv	AT yinxupingzhongpingxueweixiaozixuanliguang themethodofuavimageobjectdetectionunderfoggyweatherbystyletransfer AT yinxupingzhongpingxueweixiaozixuanliguang methodofuavimageobjectdetectionunderfoggyweatherbystyletransfer
_version_	1718406877929275392

The Method of UAV Image Object Detection under Foggy Weather by Style Transfer

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