Total Variation Denoising With Non-Convex Regularizers
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DOI: 10.1109/access.2018.2888944
Abstract: Total variation (TV) denoising has attracted considerable attention in 1-D and 2-D signal processing. For image denoising, the convex cost function can be viewed as the regularized linear least squares problem ( $\ell _{1}$ regularizer… read more here.
Keywords: total variation; convex regularizers; inline formula; non convex ... See more keywords
Learning Convex Regularizers for Optimal Bayesian Denoising
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Transactions on Signal Processing"
DOI: 10.1109/tsp.2017.2777407
Abstract: We propose a data-driven algorithm for the Bayesian estimation of stochastic processes from noisy observations. The primary statistical properties of the sought signal are specified by the penalty function (i.e., negative logarithm of the prior… read more here.
Keywords: optimal bayesian; penalty function; learning convex; convex regularizers ... See more keywords