Modeling and removal of noise using nonlocal patch-based collaborative filters, with applications to direct and inverse imaging

Alessandro Foi
Tampere University

Noise in imaging systems rarely conforms to the simple IID additive white Gaussian noise model. This tutorial provides a concise overview of alternative noise models that can be adopted in microscopy and microtomography applications. We emphasize two noise models: signal-dependent variance models and stationary spatially correlated models. We explore how to deal with them through nonlocal patch-based collaborative denoising filters such as BM3D. We also discuss the role of these noise models and filters as a versatile regularization prior for solving inverse imaging problems under the plug-and-play framework.

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