Absolute joint moments: a novel image similarity measure

Abstract

In this paper, we propose a novel approach for estimating image similarity. This measure is of importance in assessing image correspondence or image alignment and plays an important role in image registration. Currently, this problem is approached rather one-dimensionally since most registration methods consider the problem as either mono- or multi-modal. This perspective leads to the selection of some form of either the correlation coefficient (CC) or mutual information (MI) as image similarity measure (ISM). We propose a more generic framework for ISM construction, based on absolute joint moments, which can be considered as a generalization of CC. Within this framework, we propose a specific ISM that provides a different trade-off between MI and CC in terms of performance and computational cost for general registration problems. To illustrate this, we compared CC and MI with the proposed ISM and performed extensive experiments with regard to accuracy, robustness and speed. The evaluation demonstrated that the proposed absolute joint moments is a good combination of properties of CC and MI, with respect to speed and performance.