A Direct Algorithm for 1D Total Variation Denoising

Laurent Condat (1)

1 GREYC - Groupe de Recherche en Informatique, Image et Instrumentation de Caen

We propose a very fast direct, noniterative, algorithm for denoising or smoothing one-dimensional discrete signals by solving the total variation regularized least-squares problem, or the related fused lasso problem. A C code implementation is available on the web page of the author.

Mots clés: total variation; denoising; nonlinear smoothing; fused lasso; regularized least-squares; non-parametric regression; taut string algorithm; accelerated Douglas-Rachford algorithm

Domaines: Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Laurent Condat. A Direct Algorithm for 1D Total Variation Denoising. 2012. ⟨hal-00675043v1⟩