Experiments in anomalous change detection with the Viareggio 2013 trial dataset

The "Viareggio 2013 Trial" is a hyperspectral dataset obtained from multiple overflights of the Italian city of Viareggio. Careful management of panels and vehicles in the scene enabled the development of valuable ground truth information. One pair of overflights occurred at different times on the same day, and another pair took place over different days. These data were used to compare and evaluate a variety of automated approaches for discovering anomalous changes. Co-registration of the images is acknowledged to be imprecise, so part of the challenge is to identify anomalous changes in a way that is robust to this misregistration. In particular, we employed a local co-registration adjustment (LCRA) algorithm to ameliorate the effects of misregistration; we employed non-maximal suppression (NMS) to take advantage of the discrete nature of the changes; and we used canonical correlation analysis (CCA) to reduce the dimension of our data. We found that, taken together, these improved the performance of the detectors in the low false alarm rate regime of operation.

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