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Summary: Journal of Pattern Recognition Research 1 (2006) 16-32
Image Fusion and Enhancement via Empirical Mode Decomposition
Harishwaran Hariharan hari@utk.edu
Imaging, Robotics, and Intelligent Systems Lab.
Department of Electrical and Computer Engineering, University of Tennessee
410 Science & Engineering Building, Knoxville, TN 37996, USA
Andrei Gribok agribok@utk.edu
Nuclear Engineering Department, University of Tennessee
315 Pasqua Engineering, Knoxville, Tennessee 37996, USA
Mongi A. Abidi abidi@utk.edu
Andreas Koschan* akoschan@utk.edu
Imaging, Robotics, and Intelligent Systems Lab.
Department of Electrical and Computer Engineering, University of Tennessee
328 (330*) Ferris Hall, Knoxville, TN 37996, USA
Invited paper. Published January 20, 2006.
Abstract
In this paper, we describe a novel technique for image fusion and enhancement, using
Empirical Mode Decomposition (EMD). EMD is a non-parametric data-driven analysis
tool that decomposes non-linear non-stationary signals into Intrinsic Mode Functions
(IMFs). In this method, we decompose images, rather than signals, from different imaging
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