Title :
Local estimation empirical mode decomposition and its application in image fusion
Author :
Lingfei Liang ; Yongsheng Dong ; Jiexin Pu
Author_Institution :
Inf. Eng. Coll., Henan Univ. of Sci. & Technol., Luoyang, China
Abstract :
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.
Keywords :
computational complexity; image fusion; interpolation; IMF; LEEMD; bi-dimensional empirical mode decomposition; computational complexity; frequency aliasing; image fusion; interpolation method; intrinsic mode functions; local orthogonality; novel BEMD-local estimation empirical mode decomposition; Bandwidth; Computational complexity; Empirical mode decomposition; Estimation; Image fusion; Indexes; Interpolation; EMD; Image fusion; LEEMD; Local estimation;
Conference_Titel :
Information and Automation (ICIA), 2014 IEEE International Conference on
Conference_Location :
Hailar
DOI :
10.1109/ICInfA.2014.6932621