Improved change detection with local co-registration adjustments

We introduce a simple approach to compensate for the effects of residual misregistration on the performance of anomalous change detection algorithms. Using real data, both within a simulation framework for anomalous changes, and with a real anomalous change, we illustrate the approach and investigate its effectiveness.