Split Bregman algorithms for block-sparse reconstruction

Block-sparse reconstruction, which arises from the reconstruction of block-sparse signals in structured compressed sensing, is generally considered to be difficult due to the mixed-norm structure. In this paper, we propose efficient algorithms based on split Bregman iteration to solve the block-sparse reconstruction problems, including the constrained form and unconstrained form. Numerical results show that the proposed algorithms are outperform the state of the art algorithms.