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Empirical mode decomposition (EMD) is a fully data driven technique for decomposing signals into their natural scale components. However the problem of uniqueness, caused by the empirical nature of the algorithm and its sensitivity to changes in parameters, makes it difficult to perform fusion of data from multiple and heterogeneous sources. A solution to this problem is proposed using recent complex extensions of EMD which guarantees the same number of decomposition levels, that is the uniqueness of the scales. The methodology is used to address multifocus image fusion, whereby two or more partially defocused images are combined in automatic fashion so as to create an all in focus image.
Looney et al. (Fri,) studied this question.