DocumentCode :
1658114
Title :
Bivariate EMD-based image fusion
Author :
Rehman, Naveed ; Looney, David ; Rutkowski, T.M. ; Mandic, D.P.
Author_Institution :
Imperial Coll. London, London, UK
fYear :
2009
Firstpage :
57
Lastpage :
60
Abstract :
The empirical mode decomposition (EMD) algorithm is a fully data-driven method which is used to perform an adaptive decomposition of nonlinear and nonstationary signals. It has been recently illustrated that its complex extensions can be used to carry out fusion of multiple images. This is possible because the complex EMD allows comparison between common frequency scales, by aligning them within a single complex IMF. In this paper, complex extensions of EMD are proposed for the fusion of two images; the fusion methodologies are presented for both gray-level and RGB based color images. The potential of the proposed scheme is highlighted by showing its superiority to wavelet based fusion schemes, through simulations on real world multi-exposure images.
Keywords :
adaptive signal processing; image colour analysis; image fusion; RGB based color images; adaptive decomposition; bivariate empirical mode decomposition; gray-level; image fusion; nonlinear signals; nonstationary signals; Discrete cosine transforms; Discrete wavelet transforms; Educational institutions; Frequency; Image fusion; Layout; Signal analysis; Signal processing; Signal processing algorithms; Wavelet analysis; Empirical Mode Decomposition; complex signals; complex/bivariate EMD; image fusion; multi-exposure images;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Statistical Signal Processing, 2009. SSP '09. IEEE/SP 15th Workshop on
Conference_Location :
Cardiff
Print_ISBN :
978-1-4244-2709-3
Electronic_ISBN :
978-1-4244-2711-6
Type :
conf
DOI :
10.1109/SSP.2009.5278639
Filename :
5278639
Link To Document :
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