Image fusion based on an expectation maximization algorithm

Abstract

A novel image fusion method based on an expectation maximization (EM) algorithm and the discrete wavelet frame (DWF) transform is proposed. The registered images are first decomposed using the DWF transform, which is both aliasing-free and translation-invariant. The DWF decomposes the image signal into a multiresolution representation with both low-frequency coarse information and high-frequency detail information. The EM algorithm is used to fuse the low-frequency coarse information of the registered images. The informative importance measure is applied to fuse the high-frequency detail information of the registered images. The final fused image is obtained by taking the inverse transform of the composite multiresolution representations. Simulation results show that the proposed method outperforms the conventional image fusion methods.