CentraleSupélec (3, rue Joliot Curie,
Plateau de Moulon,
91192 GIF-SUR-YVETTE Cedex - France)
Abstract : Recovery of clipped audio signals is a very challenging inverse problem. Recently, it has been successfully addressed by several methods based on the sparse synthesis data model. In this work we propose an algorithm for enhancement of clipped audio signals that exploits the sparse analysis (cosparse) data model. Experiments on real audio data indicate that the algorithm has better signal restoration performance than state-of-the-art sparse synthesis declipping methods.
Srđan Kitić, Nancy Bertin, Rémi Gribonval. Audio Declipping by Cosparse Hard Thresholding. iTwist - 2nd international - Traveling Workshop on Interactions between Sparse models and Technology, Aug 2014, Namur, Belgium. ⟨hal-00922497v3⟩