Iterative image fusion using neuro fuzzy logic and applications

Image fusion to reduce uncertainty and redundancy while extracting all the useful information from the source images. Image fusion process is required for different applications, medical imaging, remote sensing, machine vision, biometrics and military applications. In this paper, an iterative neuro fuzzy logic approach utilized to fuse images from different sensors, in order to enhance visualization. The proposed work further explores comparison between neuro fuzzy based image fusion and iterative neuro fuzzy fusion technique along with quality evaluation metrics for image fusion like image quality index, mutual information measure, fusion factor, fusion symmetry, fusion index, root mean square error, peak signal to noise ratio, entropy, correlation coefficient and spatial frequency. Experimental results obtained from proposed method prove that the use of the iterative neuro fuzzy fusion can efficiently preserve the spectral information while improving the spatial resolution of the remote sensing and medical imaging.