SUB-PIXEL MAPPING BASED ON MEMETIC ALGORITHM FOR HYPERSPECTRAL IMAGERY

被引：0
|
作者：
Zhang, Yipeng [1 ]
Zhong, Yanfei [2 ,3 ]
机构：
[1] Syracuse Univ, Dept Elect Engn, Syracuse, NY 13244 USA
[2] Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan, Peoples R China
[3] Wuhan Univ, Collaborat Innovat Ctr Geospatial Technol, Wuhan, Peoples R China
来源：
2015 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | 2015年
关键词：
Sub-pixel mapping; memetic algorithm; hyperspectral remote sensing; artificial immune systems; clonal selection; local search; MAP MODEL;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In this paper, sub-pixel mapping based on memetic algorithm (SMMA) is proposed to perform the sub-pixel mapping task, including a global search and a local search. In the global search, a clonal selection algorithm can be used,. To increase the convergence speed, the local search is designed to search for a feasible solution in the neighborhood of the candidate sub-pixel mapping solutions. In addition, a new post-processing method is designed to decrease the effect of the spectral unmixing errors. The experimental results demonstrate that SMMA is superior to the traditional methods.
引用
收藏
页码：393 / 396
页数：4
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