IMPROVED COVARIANCE MATRICES FOR POINT TARGET DETECTION IN HYPERSPECTRAL DATA

被引：0
|
作者：
Sofer, Y. [1 ]
Geva, E. [1 ]
Rotman, S. R. [1 ]
机构：
[1] Ben Gurion Univ Negev, Dept Elect & Comp Engn, IL-84105 Beer Sheva, Israel
来源：
IEEE INTERNATIONAL CONFERENCE ON MICROWAVES, COMMUNICATIONS, ANTENNAS AND ELECTRONICS SYSTEMS (COMCAS 2009) | 2009年
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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：
Algorithms for point target detection in hyperspectral images use the inverse covariance matrix in order to separate a detected pixel from it surrounding noise. The inverse covariance matrix can be implemented from all the pixels or from the close surroundings of the examined pixel. We compare the different methods and conclude which method brings the best results.
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页数：4
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