A learning-based method for compressive image recovery
A novel learning-based compressive image recovery method was proposed. Autoregressive models were pre-learned to regularize the CS recovery process. Nonlocal self-similarity constraint was introduced to improve the robustness. Much better CS recovery results than current methods have been achieved.
image recovery regularization compressive sensing prior model learning non-local sparse auto-regressive model image reconstruction sparse representation