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 PGURE-SVT (Poisson-Gaussian Unbiased Risk Estimator - Singular Value Thresholding) is an algorithm designed to denoise image sequences acquired in microscopy. It exploits the correlations between consecutive frames to form low-rank matrices, which are then recovered using a technique known as nuclear norm minimization. An unbiased risk estimator for mixed Poisson-Gaussian noise is used to automate the selection of the regularization parameter, while robust noise and motion estimation maintain broad applicability to many different types of microscopy.
 
-More information on the algorithm can be found [in our paper](http://dx.doi.org/10.1016/j.ultramic.2016.05.005) in *Ultramicroscopy*.
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 If you use this code in a publication, please cite our work:
 
 > T. Furnival, R. K. Leary and P. A. Midgley, "Denoising time-resolved microscopy sequences with singular value thresholding", *Ultramicroscopy*, vol. 178, pp. 112–124, 2017. DOI:[10.1016/j.ultramic.2016.05.005](http://dx.doi.org/10.1016/j.ultramic.2016.05.005)