Image Sequence Fusion Using a Shift-Invariant Wavelet Transform
ICIP '97 Proceedings of the 1997 International Conference on Image Processing (ICIP '97) 3-Volume Set-Volume 3 - Volume 3
Multiscale image fusion using complex extensions of EMD
IEEE Transactions on Signal Processing
Multispectral image visualization through first-order fusion
IEEE Transactions on Image Processing
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Image fusion has emerged as a promising area of research and a bivariate empirical mode decomposition based fusion scheme has recently been proposed in the literature. In this paper, a hybrid fusion scheme combining self-fractional Fourier function (SFFF) decomposition and multivariate empirical mode decomposition is proposed. In the proposed image fusion technique, images to be fused are decomposed into SFFF images. The SFFF images are further decomposed into intrinsic mode functions (IMFs) using multivariate empirical mode decomposition (MEMD). Corresponding IMFs of same decomposition level of SFFF images are fused using local variance based adaptive weight fusion rule to obtain fused IMF images. The fused image is obtained by applying inverse transformation on fused IMF images. The proposed technique provides flexibility in the number of functions in the SFFF decomposition, transform before SFFF decomposition, and the types of source images (real and complex) to be fused. Simulations are performed for fusion of test images with different SFFF decomposition levels and the results are compared with other existing methods. It is seen that the simulation results are comparable to the existing schemes.