Restoration of shadows in multispectral imagery using surface reflectance relationships with nearby similar areas
文献类型：期刊论文
| 作者 | Wen, Zhaofei1,2 ; Shao, Guofan3; Mirza, Zakaria A.1; Chen, Jilong1; Lu, Mingquan1; Wu, Shengjun1
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| 刊名 | INTERNATIONAL JOURNAL OF REMOTE SENSING
 |
| 出版日期 | 2015 |
| 卷号 | 36期号:16页码:4195-4212 |
| ISSN号 | 0143-1161 |
| DOI | 10.1080/01431161.2015.1079343 |
| 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 |
| WOS记录号 | WOS:000359970900008 |
| 出版者 | TAYLOR & FRANCIS LTD |
| 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 |
| 推荐引用方式 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. |
入库方式： OAI收割
来源：重庆绿色智能技术研究院
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