Authors: Michel Ouendeno, Samuel P. Kozaitis
Addresses: Florida Institute of Technology, Department of Electrical and Computer Engineering, 150 W. University Blvd., Melbourne, FL 32901, USA. ' Florida Institute of Technology, Department of Electrical and Computer Engineering, 150 W. University Blvd., Melbourne, FL 32901, USA
Abstract: We applied an image fusion approach that uses different wavelet transforms for the forward and reconstruction transforms to efficiently compact energy for improved reconstruction. In addition, we used denoising to reduce the error induced by this approach. We found that using such an approach generally increases the Average Relative Entropy (ARE) of the fused result when compared to a conventional image fusion method.
Keywords: denoising; feature extraction; image fusion; thresholding; wavelet transforms; average relative entropy.
International Journal of Signal and Imaging Systems Engineering, 2008 Vol.1 No.2, pp.127 - 134
Published online: 24 Oct 2008 *Full-text access for editors Access for subscribers Purchase this article Comment on this article