Image Fusion Quality Measure Based on a Multi-scale Approach

Abstract

In this paper, we present a general purpose and non-reference multi-scale structural similarity measure for objective quality assessment of image fusion. We aim to extend Piella’s measure [1] in several ways, within a multi-scale approach, by making multiple Piella’s measure image evaluations at different image scales, fusing the result into a single evaluation. The main advantage of multi-scale methods lie in its ability to capture the relevant and useful image information at different resolutions. We validated our proposal in different imaging application scenarios, particularly in a 2015 multi-exposure image fusion database that provides human subjective evaluations. Experimental results show that our approach achieves high correlation with the subjective scores provided by the database and makes a significant improvement over the previous Piella’s single-scale fusion quality measure.