Local Estimation Empirical Mode Decomposition And Its Application In Image Fusion

被引：0
|
作者：
Liang, Lingfei [1 ]
Dong, Yongsheng [1 ]
Pu, Jiexin [1 ]
机构：
[1] Henan Univ Sci & Technol, Informat Engn Coll, Luoyang, Henan, Peoples R China
来源：
2014 IEEE INTERNATIONAL CONFERENCE ON INFORMATION AND AUTOMATION (ICIA) | 2014年
关键词：
EMD; LEEMD; Local estimation; Image fusion;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The interpolation causes the frequency aliasing in intrinsic mode functions (IMF) in bi-dimensional empirical mode decomposition (BEMD). The local orthogonality or the computational complexity of the improved BEMDs can not be met. In this paper, a novel BEMD - local estimation empirical mode decomposition (LEEMD) is proposed. Particularly, the local estimation instead of the interpolation without changing the framework of EMD is proposed to solve the problem. LEEMD will be applied in image fusion based on the proposed background/detail rule. In experiments, the objective and subjective experiments show that LEEMD and its application is effective.
引用
收藏
页码：31 / 34
页数：4
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