Variational algorithms to remove stationary noise. Application to microscopy imaging.
Résumé
A framework and an algorithm are presented in order to remove stationary noise from images. This algorithm is called VSNR (Variational Stationary Noise Remover). It can be interpreted both as a restoration method in a Bayesian framework and as a cartoon+texture decomposition method. In numerous denoising applications the white noise assumption fails: structured patterns (e.g. stripes) appear in the images. The model described here addresses these cases. Applications are presented with images acquired using different modalities: scan- ning electron microscope, FIB-nanotomography, and an emerging fluorescence microscopy technique called SPIM (Selective Plane Illumination Microscope).
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