Well-established techniques for comparing images frequently place them side-by-side. A major drawback of such approaches is that they do not scale well. Other image comparison methods encode differences in images by abstract parameters like color. In this case information about the underlying image data gets lost.
We present VAICo - Visual Analysis for Image Comparison. This new method for visualizing differences and similarities in large sets of images preserves contextual information, but also allows the detailed analysis of subtle variations. Our approach identifies local changes and applies cluster analysis techniques to embed them in a hierarchy. The results of this process are then presented in an interactive web application, which allows users to rapidly explore the space of differences and drill-down on particular features.
The approach was presented at VAST 2013, further information can be found here.
Johanna Schmidt, M. Eduard Gröller and Stefan Bruckner: VAICo - Visual Analysis for Image Comparison. IEEE Transactions on Visualization and Computer Graphics 19(12), December 2013, pp. 2090-2099, IEEE Educational Activities Department, Piscataway, NJ, USA
You can test our approach online with the following datasets: