A Mixed Property-Based Automatic Shadow Detection Approach for VHR Multispectral Remote Sensing Images

doi:10.3390/app8101883

CIOMP OpenIR

	A Mixed Property-Based Automatic Shadow Detection Approach for VHR Multispectral Remote Sensing Images
	Han, Hongyin 1,2; Han, Chengshan1 ; Xue, Xucheng1 ; Hu, Changhong 1; Huang, Liang1,2 ; Li, Xiangzhi1 ; Lan, Taiji 1; Wen, Ming1,2
	2018-10-01
发表期刊	APPLIED SCIENCES-BASEL
ISSN	2076-3417
卷号	8 期号:10 页码:28
通讯作者	Xue, Xucheng(xue0818@163.com)
摘要	Shadows in very high-resolution multispectral remote sensing images hinder many applications, such as change detection, target recognition, and image classification. Though a wide variety of significant research has explored shadow detection, shadow pixels are still more or less omitted and are wrongly confused with vegetation pixels in some cases. In this study, to further manage the problems of shadow omission and vegetation misclassification, a mixed property-based shadow index is developed for detecting shadows in very high-resolution multispectral remote sensing images based on the difference of the hue component and the intensity component between shadows and nonshadows, and the difference of the reflectivity of the red band and the near infrared band between shadows and vegetation cover in nonshadows. Then, the final shadow mask is achieved, with an optimal threshold automatically obtained from the index image histogram. To validate the effectiveness of our approach for shadow detection, three test images are selected from the multispectral WorldView-3 images of Rio de Janeiro, Brazil, and are tested with our method. When compared with other investigated standard shadow detection methods, the resulting images produced by our method deliver a higher average overall accuracy (95.02%) and a better visual sense. The highly accurate data show the efficacy and stability of the proposed approach in appropriately detecting shadows and correctly classifying shadow pixels against the vegetation pixels for very high-resolution multispectral remote sensing images.
关键词	invariant color space multispectral images shadow detection shadow omission threshold vegetation misclassification very high-resolution
DOI	10.3390/app8101883
关键词[WOS]	RESOLUTION SATELLITE IMAGES ; COLOR ; FEATURES
收录类别	SCI
语种	英语
资助项目	Key Project on National Defense Science and Technology Innovation of the Chinese Academy of Sciences[41275487-X]
项目资助者	Key Project on National Defense Science and Technology Innovation of the Chinese Academy of Sciences
WOS研究方向	Chemistry ; Materials Science ; Physics
WOS类目	Chemistry, Multidisciplinary ; Materials Science, Multidisciplinary ; Physics, Applied
WOS记录号	WOS:000448653700178
出版者	MDPI
引用统计
文献类型	期刊论文
条目标识符	http://ir.ciomp.ac.cn/handle/181722/60552
专题	中国科学院长春光学精密机械与物理研究所
通讯作者	Xue, Xucheng
作者单位	1.Chinese Acad Sci, Changchun Inst Opt Fine Mech & Phys, Changchun 130033, Jilin, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
推荐引用方式 GB/T 7714	Han, Hongyin,Han, Chengshan,Xue, Xucheng,et al. A Mixed Property-Based Automatic Shadow Detection Approach for VHR Multispectral Remote Sensing Images[J]. APPLIED SCIENCES-BASEL,2018,8(10):28.
APA	Han, Hongyin.,Han, Chengshan.,Xue, Xucheng.,Hu, Changhong.,Huang, Liang.,...&Wen, Ming.(2018).A Mixed Property-Based Automatic Shadow Detection Approach for VHR Multispectral Remote Sensing Images.APPLIED SCIENCES-BASEL,8(10),28.
MLA	Han, Hongyin,et al."A Mixed Property-Based Automatic Shadow Detection Approach for VHR Multispectral Remote Sensing Images".APPLIED SCIENCES-BASEL 8.10(2018):28.

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