Video fusion performance assessment based on spatial-temporal phase congruency

Most image or video fusion quality metrics are designed to evaluate different video fusion methods for spatial-temporal extraction. And there is limited research on the evaluation of spatial-temporal consistency. In this paper, a video fusion quality metric is proposed to evaluate different fusion methods for spatial-temporal consistency, where spatial-temporal phase congruency is employed as a feature to be compared and 3D zero-mean normalized cross-correlation is employed as the similarity measure. Firstly, the spatial-temporal phase congruency maps for input and fused videos are computed using a set of predefined 3D Log-Gabor filters. Then the spatial-temporal phase congruency maps are divided into many non-overlapped spatial-temporal blocks and a local block-based quality metric is defined by performing 3D zero-mean normalized cross-correlation on the relevant spatial-temporal phase congruency maps of the input and fused videos. Finally, the global quality metric is constructed as the weighted average of all the block-based quality metrics. The required local and global weights are defined by the spatial-temporal structure tensor. Several sets of experiments demonstrate the validity and feasibility of the proposed metric. Moreover, the proposed metric shows higher stability and robustness than some other metrics in a noisy environment. (c) 2014 Elsevier B.V. All rights reserved.