Temporal Consolidation Strategy for Ground Based Image Displacement Time Series

In this paper, we propose a new method to combine displacement measurements from images with a low signal to noise ratio. The method takes advantage of the temporal redundancy of displacements that can be calculated from different image pairs to combine them in a single relative displacement time series robust to outliers. The method has only two parameters which determines the smoothness of the result. The proposed algorithm has been tested on displacements calculated from ground based stereo images of the Laurichard rock glacier. On the test data, our method outperforms the traditional inversion method by providing relative displacement time series with negligible noise and no outlier.