Bayesian selection for the l2-Potts model regularization parameter: 1D piecewise constant signal denoising

27 Aug 2016Jordan FreconNelly PustelnikNicolas DobigeonHerwig WendtPatrice Abry

Piecewise constant denoising can be solved either by deterministic optimization approaches, based on the Potts model, or by stochastic Bayesian procedures. The former lead to low computational time but require the selection of a regularization parameter, whose value significantly impacts the achieved solution, and whose automated selection remains an involved and challenging problem... (read more)

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