L0-Norm-Based Sparse Representation Through Alternate Projections

We present a simple and robust method for finding sparse representations in overcomplete transforms, based on minimization of the L0-norm. Our method is better than current solutions based on minimization of the L1-norm in terms of energy compaction. These results strongly question the equivalence of minimizing both norms in real conditions. We also show application to in-painting (interpolation of lost pixels).