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Image fusion using multivariate and multidimensional EMD.

ur Rehman, Naveed and Khan, M Murtaza and Sohaib, Ishaq and Jehanzaib, Muhammad and Ehsan, Shoaib and McDonald-Maier, Klaus D (2015) Image fusion using multivariate and multidimensional EMD. In: 2014 IEEE International Conference on Image Processing (ICIP), 2014-10-27 - 2014-10-30, Paris.

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We present a novel methodology for the fusion of multiple (two or more) images using the multivariate extension of empirical mode decomposition (MEMD). Empirical mode decomposition (EMD) is a data-driven method which decomposes input data into its intrinsic oscillatory modes, known as intrinsic mode functions (IMFs), without making a priori assumptions regarding the data. We show that the multivariate and multidimensional extensions of EMD are suitable for image fusion purposes. We further demonstrate that while multidimensional extensions, by design, may seem more appropriate for tasks related to image processing, the proposed multivariate extension outperforms these in image fusion applications owing to its mode-alignment property for IMFs. Case studies involving multi-focus image fusion and pan-sharpening of multi-spectral images are presented to demonstrate the effectiveness of the proposed method.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: 2014 IEEE International Conference on Image Processing (ICIP)
Uncontrolled Keywords: Empirical mode decomposition (EMD); Multivariate EMD (MEMD); Bidimensional EMD; Multi-focus image fusion; Pan-sharpening
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health
Faculty of Science and Health > Computer Science and Electronic Engineering, School of
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 23 Jul 2015 12:13
Last Modified: 15 Jan 2022 00:24

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