Title :
Multiscale Image Fusion Using Complex Extensions of EMD
Author :
Looney, David ; Mandic, Danilo P.
Author_Institution :
Imperial Coll. London, London
fDate :
4/1/2009 12:00:00 AM
Abstract :
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.
Keywords :
image fusion; empirical mode decomposition; multiscale image fusion; signal decomposition; Complex-valued signal processing; empirical mode decomposition (EMD); image fusion;
Journal_Title :
Signal Processing, IEEE Transactions on
DOI :
10.1109/TSP.2008.2011836