Structured spatial domain image and data comparison metrics

Often, images or datasets have to be compared to facilitate choices of visualization and simulation parameters respectively. Common comparison techniques include side-by-side viewing and juxtaposition, in order to facilitate visual verification of verisimilitude. We propose quantitative techniques which accentuate differences in images and datasets. The comparison is enabled through a collection of partial metrics which, essentially, measure the lack of correlation between the datasets or images being compared. That is, they attempt to expose and measure the extent of the inherent structures in the difference between images or datasets. Besides yielding numerical attributes, the metrics also produce images which can visually highlight differences. Our metrics are simple to compute and operate in the spatial domain. We demonstrate the effectiveness of our metrics through examples for comparing images and datasets.