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In this paper, a novel objective evaluation metric for image fusion ispresented. Remarkable and attractive points of the proposed metric are that ithas no parameter, the result is probability in the range of [0, 1] and it isfree from illumination dependence. This metric is easy to implement and theresult is computed in four steps: (1) Smoothing the images using Gaussianfilter. (2) Transforming images to a vector field using Del operator. (3)Computing the normal distribution function ({\mu},{\sigma}) for eachcorresponding pixel, and converting to the standard normal distributionfunction. (4) Computing the probability of being well-behaved fusion method asthe result. To judge the quality of the proposed metric, it is compared tothirteen well-known non-reference objective evaluation metrics, where eightfusion methods are employed on seven experiments of multimodal medical images.The experimental results and statistical comparisons show that in contrast tothe previously objective evaluation metrics the proposed one performs better interms of both agreeing with human visual perception and evaluating fusionmethods that are not performed at the same level.

An Objective Evaluation Metric for image fusion based on Del Operator