About neuro fuzzy based image fusion

ABSTRACT:

Neural Network and Fuzzy Logic approach can be used for sensor fusion. Such a sensor fusion could belong to a class of sensor fusion in which case the features could be input and decision could be output. The help of Neuro-fuzzy of fuzzy systems can achieve sensor fusion. The system can be trained from the input data obtained from the sensors. The basic concept is to associate the given sensory inputs with some decision outputs. After developing the system. another group of input data is used to evaluate the performance of the system.

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.