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Convex 1-D Total Variation Denoising with Non-convex Regularization
2015
IEEE Signal Processing Letters
Total variation (TV) denoising is an effective noise suppression method when the derivative of the underlying signal is known to be sparse. TV denoising is defined in terms of a convex optimization problem involving a quadratic data fidelity term and a convex regularization term. A non-convex regularizer can promote sparsity more strongly, but generally leads to a non-convex optimization problem with non-optimal local minima. This letter proposes the use of a non-convex regularizer constrained
doi:10.1109/lsp.2014.2349356
fatcat:dhjn75rqlngflbkzwgopevctnu