VIDEO ERROR CONCEALMENT USING SPARSE RECOVERY AND LOCAL DICTIONARIES

Video error concealment is a post-processing technique that conceals the errors in a decoded video sequence based on data available only at the decoder. Most of the current techniques adopt the approach that recovers the Motion Vector (MV) of a lost image block, uses that MV to look for data to fill in the blank then performs some refinements. We propose a method that does not rely on MV recovery, but essentially bases on sparse representation of image patches on local temporal dictionaries. Experiment results show a large improvement over Boundary Matching Algoritm (BMA), the standard method used in reference software for H.264 video codec