UNSPECIFIED (2015) 'Multi-Scale pixel-based image fusion using multivariate empirical mode decomposition.' Sensors (Switzerland), 15 (5). 10923 - 10947. ISSN 1424-8220

Preview

Text sensors-15-10923.pdf - Published Version Available under License Creative Commons Attribution. Download (3MB) | Preview

Abstract

© 2015 by the authors; licensee MDPI, Basel, Switzerland. A novel scheme to perform the fusion of multiple images using the multivariate empirical mode decomposition (MEMD) algorithm is proposed. Standard multi-scale fusion techniques make a priori assumptions regarding input data, whereas standard univariate empirical mode decomposition (EMD)-based fusion techniques suffer from inherent mode mixing and mode misalignment issues, characterized respectively by either a single intrinsic mode function (IMF) containing multiple scales or the same indexed IMFs corresponding to multiple input images carrying different frequency information. We show that MEMD overcomes these problems by being fully data adaptive and by aligning common frequency scales from multiple channels, thus enabling their comparison at a pixel level and subsequent fusion at multiple data scales. We then demonstrate the potential of the proposed scheme on a large dataset of real-world multi-exposure and multi-focus images and compare the results against those obtained from standard fusion algorithms, including the principal component analysis (PCA), discrete wavelet transform (DWT) and non-subsampled contourlet transform (NCT). A variety of image fusion quality measures are employed for the objective evaluation of the proposed method. We also report the results of a hypothesis testing approach on our large image dataset to identify statistically-significant performance differences.

Item Type:	Article
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User:	Jim Jamieson
Date Deposited:	30 Apr 2015 09:29
Last Modified:	08 Jan 2019 22:15
URI:	http://repository.essex.ac.uk/id/eprint/13642

Actions (login required)

View Item