A novel statistical fusion rule for image fusion and its comparison in non subsampled contourlet transform domain and wavelet domain
Computer Vision and Pattern Recognition
2012-05-09 v1 Statistics Theory
Statistics Theory
Abstract
Image fusion produces a single fused image from a set of input images. A new method for image fusion is proposed based on Weighted Average Merging Method (WAMM) in the NonSubsampled Contourlet Transform (NSCT) domain. A performance analysis on various statistical fusion rules are also analysed both in NSCT and Wavelet domain. Analysis has been made on medical images, remote sensing images and multi focus images. Experimental results shows that the proposed method, WAMM obtained better results in NSCT domain than the wavelet domain as it preserves more edges and keeps the visual quality intact in the fused image.
Keywords
Cite
@article{arxiv.1205.1648,
title = {A novel statistical fusion rule for image fusion and its comparison in non subsampled contourlet transform domain and wavelet domain},
author = {Manu V T and Philomina Simon},
journal= {arXiv preprint arXiv:1205.1648},
year = {2012}
}
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19 pages