Affiliations: [a] Concordia Institute for Information Systems Engineering, Concordia University, Montréal, Quebec, Canada H3G 1T7. E-mail: hamza@ciise.concordia.ca | [b] Tality Corporation, Cary, NC 27511, USA. E-mail: yhe@tality.com | [c] Department of Electrical and Computer Engineering, North Carolina State University, Raleigh, NC 27695-7914, USA. E-mail: ahk@ncsu.edu | [d] Laboratory for Information and Decision Systems, Massachusetts Institute of Technology, Cambridge, MA 02139-4307, USA. E-mail: willsky@mit.edu
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Abstract: Pixel level image fusion refers to the processing and synergistic combination of information gathered by various imaging sources to provide a better understanding of a scene. We formulate the image fusion as an optimization problem and propose an information theoretic approach in a multiscale framework to obtain its solution. A biorthogonal wavelet transform of each source image is first calculated, and a new Jensen-Rényi divergence-based fusion algorithm is developed to construct composite wavelet coefficients according to the measurement of the information patterns inherent in the source images. Experimental results on fusion of multi-sensor navigation images, multi-focus optical images, multi-modality medical images and multi-spectral remote sensing images are presented to illustrate the proposed fusion scheme.
