Abstract
Image fusion is the process of reducing uncertainty and minimizing redundancy while extracting all the useful information from the source images. Image fusion process is required for different applications like medical imaging, remote sensing, machine vision, biometrics and military applications. In this paper, an iterative fuzzy logic approach utilized to fuse images from different sensors, in order to enhance visualization. The proposed workfurther explores comparison between fuzzy based image fusion and iterative fuzzy fusion technique along with quality evaluation indices for image fusion like image quality index, mutual information measure, root mean square error, peak signal to noise ratio, entropy and correlation coefficient. Experimental results obtained from fusion process prove that the use of the proposed iterative fuzzy fusion can efficiently preserve the spectral information while improving the spatial resolution of the remote sensing images and medical imaging.
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Dammavalam, S.R., Maddala, S., Krishna Prasad, M.H.M. (2013). Iterative Image Fusion Using Fuzzy Logic with Applications. In: Meghanathan, N., Nagamalai, D., Chaki, N. (eds) Advances in Computing and Information Technology. Advances in Intelligent Systems and Computing, vol 177. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31552-7_16
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DOI: https://doi.org/10.1007/978-3-642-31552-7_16
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