A Novel Method of Medical Image Fusion Based on Bidimensional Empirical Mode Decomposition

In this paper, a novel method of medical image fusion based on bidimensional empirical mode decomposition (BEMD) is proposed with the aim to improve the quality of fused medical images. BEMD is first used in this paper to decompose medical images into bidimensional intrinsic mode functions (BIMFs) and residue. In this paper m-BIMFs is proposed for the first time, which has larger scale and better feature than BIMFs. Finally, m-PCNN(Pulse Coupled Neural Network), an improved PCNN mode, is used to fuse corresponding m-BIMFs. The experimental results demonstrate that our method is successfully applied to medical image fusion and better than traditional wavelet fusion , pyramid fusion and unimproved m-PCNN fusion.

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