We present a fast smoother and interpolator for time series. It is based on Whittaker smoother. The amount of smoothing is optimized with the so-called V-curve, a variation on the L-curve. The algorithm is very fast, thanks to the use of sparse matrices. It handles (even many) missing data points with ease. Envelopes can be estimated by expectile smoothing.

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Persistent URL dx.doi.org/10.1109/Multi-Temp.2017.8076705, hdl.handle.net/1765/102636
Conference 9th International Workshop on the Analysis of Multitemporal Remote Sensing Images, MultiTemp 2017
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Citation
Eilers, P.H.C, Pesendorfer, V. (Valentin), & Bonifacio, R. (Rogerio). (2017). Automatic Smoothing of Remote Sensing Data. In 2017 9th International Workshop on the Analysis of Multitemporal Remote Sensing Images, MultiTemp 2017. doi:10.1109/Multi-Temp.2017.8076705