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

文献类型：期刊论文

作者Wen, Ming1,2; Lan, Taiji2; Li, Xiangzhi2; Huang, Liang1,2; Hu, Changhong2; Xue, Xucheng2; Han, Chengshan2; Han, Hongyin1,2
刊名APPLIED SCIENCES-BASEL
出版日期2018-10-01
卷号8期号:10页码:28
关键词invariant color space multispectral images shadow detection shadow omission threshold vegetation misclassification very high-resolution
ISSN号2076-3417
DOI10.3390/app8101883
通讯作者Xue, Xucheng(xue0818@163.com)
英文摘要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.
WOS关键词RESOLUTION SATELLITE IMAGES ; COLOR ; FEATURES
资助项目Key Project on National Defense Science and Technology Innovation of the Chinese Academy of Sciences[41275487-X]
WOS研究方向Chemistry ; Materials Science ; Physics
语种英语
WOS记录号WOS:000448653700178
出版者MDPI
资助机构Key Project on National Defense Science and Technology Innovation of the Chinese Academy of Sciences
源URL[http://ir.ciomp.ac.cn/handle/181722/60553]  
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.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
2.Chinese Acad Sci, Changchun Inst Opt Fine Mech & Phys, Changchun 130033, Jilin, Peoples R China
推荐引用方式
GB/T 7714		 Wen, Ming,Lan, Taiji,Li, Xiangzhi,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 Wen, Ming.,Lan, Taiji.,Li, Xiangzhi.,Huang, Liang.,Hu, Changhong.,...&Han, Hongyin.(2018).A Mixed Property-Based Automatic Shadow Detection Approach for VHR Multispectral Remote Sensing Images.APPLIED SCIENCES-BASEL,8(10),28.
MLA Wen, Ming,et al."A Mixed Property-Based Automatic Shadow Detection Approach for VHR Multispectral Remote Sensing Images".APPLIED SCIENCES-BASEL 8.10(2018):28.

入库方式： OAI收割

来源：长春光学精密机械与物理研究所

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