Title :
Image Fusion Algorithm Using Pyramidal Empirical Mode Decomposition
Author :
Li, Hui ; Zheng, Youzhi
Author_Institution :
Coll. of Software, Shenyang Normal Univ., Shenyang, China
Abstract :
Multi-scale decomposition (MSD) approaches are very useful in image processing and play an important role in image fusion algorithm. This paper proposes a novel image fusion algorithm using pyramidal empirical mode decomposition (PEMD). The principle of PEMD consists of performing a pyramid transform on intrinsic mode functions (IMF) and the residual image of empirical mode decomposition (EMD). The input images are decomposed into a sequence of detail pyramidal images at different levels of resolution and an approximation image by PEMD. Fusion algorithm is performed on the input images decompositions to produce the composite PEMD representation and then the inverse PEMD transform is applied to obtain the fused image. The experimental results show that the fusion algorithm by using PEMD gives more encouraging and effective performance than EMD and traditional pyramid fusion algorithms.
Keywords :
approximation theory; image fusion; image representation; image resolution; image sequences; approximation theory; image fusion algorithm; image representation; image resolution; image sequence; intrinsic mode function; multiscale decomposition approach; pyramidal empirical mode decomposition; Discrete wavelet transforms; Feature extraction; Fourier transforms; Image fusion; Image processing; Image sensors; Layout; Sensor fusion; Signal processing algorithms; Software algorithms; Multi-Scale Decomposition (MSD); Pyramidal Empirical Mode Decomposition (PEMD); image fusion; perfect reconstruction;
Conference_Titel :
Hybrid Intelligent Systems, 2009. HIS '09. Ninth International Conference on
Conference_Location :
Shenyang
Print_ISBN :
978-0-7695-3745-0
DOI :
10.1109/HIS.2009.38