Image Fusion Algorithm Using Pyramidal Empirical Mode Decomposition
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.
image fusion Multi-Scale Decomposition (MSD) Pyramidal Empirical Mode Decomposition (PEMD) perfect reconstruction
Hui Li Youzhi Zheng
College of Software Shenyang Normal University Shenyang, China Department of Computer Science & Technology Tsinghua University Beijing, China
国际会议
2009 Ninth International Conference on Hybrid Intelligent Systems(第九届混合智能系统国际会议 HIS 2009)
沈阳
英文
1-6
2009-08-12（万方平台首次上网日期，不代表论文的发表时间）