Evaluation of Image Fusion Algorithms

ABSTRACT: There is a growing need for tools performance or quality evaluation in order to compare results obtained with different image fusion algorithms. This analysis can be used to select a specific algorithm for a particular type fusion dataset. Picture quality is a characteristic of an image that measures the perceived image degradation (typically, compared to an ideal or perfect image). Imaging systems may introduce some amounts of distortion or artifacts in the signal, so the quality assessment is an important problem. There are several techniques and metrics that can be objectively measured and evaluated automatically by a computer program. Therefore, they can be classified as complete reference methods (FR) and No-reference methods (NR). In the methods of image quality assessment FR, the quality of a test image is evaluated by comparing a reference image that is supposed to have the perfect quality. NR metrics try to assess the quality of an image without any reference to the original.