Semi-local total variation for regularization of inverse problems

We propose the discrete semi-local total variation (SLTV) as a new regularization functional for inverse problems in imaging. The SLTV favors piecewise linear images; so the main drawback of the total variation (TV), its clustering effect, is avoided. Recently proposed primal-dual methods allow to solve the corresponding optimization problems as easily and efficiently as with the classical TV.

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