Structured spatial domain image and data comparison metrics

Authors:
Nivedita Sahasrabudhe;John E. West;Raghu Machiraju;Mark Janus
Affiliations:
NSF Engineering Research Center, Mississippi State University;DoD High Performance Computing Center, Information Technology Laboratory, USAE Waterways Experiment Station and NSF Engineering Research Center, Mississippi State University;Department of Computer Science, NSF Engineering Research Center, Mississippi State University;Department of Aerospace Engineering, NSF Engineering Research Center, Mississippi State University
Venue:
VIS '99 Proceedings of the conference on Visualization '99: celebrating ten years
Year:
1999

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Abstract

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. In this paper, 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.