Arid
DOI10.1007/s12652-015-0255-1
On the study of fusion techniques for bad geological remote sensing image
Li, Xiang1; Wang, Lingling2
通讯作者Li, Xiang
来源期刊JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING
ISSN1868-5137
EISSN1868-5145
出版年2015
卷号6期号:1页码:141-149
英文摘要

One of the crucial steps in the fusion of remote sensing image is the selection of proper fusion techniques. In this paper, we focused on the bad geology, such as desert, permafrost, saltmarsh, etc., in Yuli Rob Village, Xinjiang Province. The selection of best band in remote sensing images is treated as a combinational optimization problem, and an optimum index factor method is proposed for the selection of best band in remote sensing images. Based on the analysis of general fusion techniques used in remote sensing image, three representative techniques, i.e., Gram-Schmidt, color normalized transformation, and principle component transformation are used for the fusion of bad geological remote sensing images. Experimental results indicated that the techniques used in this study improve the image spatial information, and they can maintain the spectral feature of multi-spectral images.


英文关键词Remote sensing image Fusion Bad geology
类型Article
语种英语
国家Peoples R China
收录类别SCI-E
WOS记录号WOS:000351243300012
WOS关键词TRANSFORM
WOS类目Computer Science, Artificial Intelligence ; Computer Science, Information Systems ; Telecommunications
WOS研究方向Computer Science ; Telecommunications
资源类型期刊论文
条目标识符http://119.78.100.177/qdio/handle/2XILL650/188203
作者单位1.China Univ Geosci, Sch Comp Sci, Wuhan 430074, Peoples R China;
2.Wuhan Univ Engn Sci, Engn & Elect Informat Dept, Wuhan 430200, Peoples R China
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Li, Xiang,Wang, Lingling. On the study of fusion techniques for bad geological remote sensing image[J],2015,6(1):141-149.
APA Li, Xiang,&Wang, Lingling.(2015).On the study of fusion techniques for bad geological remote sensing image.JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING,6(1),141-149.
MLA Li, Xiang,et al."On the study of fusion techniques for bad geological remote sensing image".JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING 6.1(2015):141-149.
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