Restoration of shadows in multispectral imagery using surface reflectance relationships with nearby similar areas
Wen, Zhaofei1,2; Shao, Guofan3; Mirza, Zakaria A.1; Chen, Jilong1; Lu, Mingquan1; Wu, Shengjun1
刊名INTERNATIONAL JOURNAL OF REMOTE SENSING
2015
卷号36期号:16页码:4195-4212
ISSN号0143-1161
DOI10.1080/01431161.2015.1079343
通讯作者Wu, SJ (reprint author), Chinese Acad Sci, Chongqing Inst Green & Intelligent Technol, Chongqing 400714, Peoples R China.
英文摘要The presence of shadows in optical satellite images limits the application of remote-sensing technology. It is important to restore shadow radiance information for improving information extraction from remote-sensing images. Several shadow-restoration methods have been developed using complex statistical relationships between shadowed areas and their nearby sunlit areas. In this study, a simple shadow-restoration approach was proposed based on the surface reflectance equality relationship (RER) under the assumption that the surface reflectance of a feature in the shadowed area is equal to that of the same feature in the nearby sunlit area. This approach reduces the number of parameters, thus reducing the error propagated by the uncertainties of extra parameters. The new RER method was tested with three multispectral images with different shadow features. By comparing RER with the widely used mean and variance transformation, the RER was shown to be capable of restoring the image colours, texture, tone, and brightness of the shadowed areas to a visually satisfactory level. Quantitative analysis suggests that RER can help to restore the reflectance of shadow features accurately and has robust performance for a variety of land-surface types. Moreover, RER can be effectively used to restore the spectral shape information of shadow features, which is particularly important when applying RER to the restoration of multispectral imagery for the purpose of image classification.
资助项目Chongqing Science & Technology Commission[cstc2014jcyjA00017] ; Chongqing Science & Technology Commission[cstc2012ggB20001] ; Chongqing Science & Technology Commission[cstc2015jcyjA1149] ; National Nature Science Foundation of China[41371394]
WOS研究方向Remote Sensing ; Imaging Science & Photographic Technology
语种英语
出版者TAYLOR & FRANCIS LTD
WOS记录号WOS:000359970900008
内容类型期刊论文
源URL[http://119.78.100.138/handle/2HOD01W0/1872]  
专题生态过程与重建研究中心
通讯作者Wu, Shengjun
作者单位1.Chinese Acad Sci, Chongqing Inst Green & Intelligent Technol, Chongqing 400714, Peoples R China
2.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China
3.Purdue Univ, Dept Forestry & Nat Resources, W Lafayette, IN 47907 USA
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GB/T 7714
Wen, Zhaofei,Shao, Guofan,Mirza, Zakaria A.,et al. Restoration of shadows in multispectral imagery using surface reflectance relationships with nearby similar areas[J]. INTERNATIONAL JOURNAL OF REMOTE SENSING,2015,36(16):4195-4212.
APA Wen, Zhaofei,Shao, Guofan,Mirza, Zakaria A.,Chen, Jilong,Lu, Mingquan,&Wu, Shengjun.(2015).Restoration of shadows in multispectral imagery using surface reflectance relationships with nearby similar areas.INTERNATIONAL JOURNAL OF REMOTE SENSING,36(16),4195-4212.
MLA Wen, Zhaofei,et al."Restoration of shadows in multispectral imagery using surface reflectance relationships with nearby similar areas".INTERNATIONAL JOURNAL OF REMOTE SENSING 36.16(2015):4195-4212.
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