  Image fusion is the process of integrating multiple images of the same scene
into a single fused image to reduce 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, medical imaging, machine vision, biometrics and military applications
where quality and critical information is required. In this paper, image fusion
using fuzzy and neuro fuzzy logic approaches utilized to fuse images from
different sensors, in order to enhance visualization. The proposed work further
explores comparison between fuzzy based image fusion and neuro fuzzy fusion
technique along with quality evaluation indices 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 fusion process prove that the use of the neuro fuzzy based image fusion
approach shows better performance in first two test cases while in the third
test case fuzzy based image fusion technique gives better results.
