A Novel Quality Image Fusion Assessment Based on Maximum Codispersion

摘要

In this paper, we present a novel objetive measure for image fusion based on the codispersion quality index, following the structure of Piella's metric. The measure quantifies the maximum local similarity between two images for many directions using the maximum codispersion quality index. This feature is not commonly assessed by other measures of similarity between images. To vizualize the performance of the maximum codispersion quality index we suggested two graphical tools. The proposed fusion measure is compared to image structural similarity based metrics of the state-of-art. Different experiments performed on several databases show that our metric is consistent with human visual evaluation and can be applied to evaluate different image fusion schemes.