On compensating unknown pixel behaviors for image sensors with embedded processing

Some smart imagers embed image processing operations or Compressive Sensing at the focal plane level. This process introduces artifacts due to technology dispersion and unpredictable behaviors. This article presents a generic algorithm structure well suited for compensating block artifacts by appropriate post processing operations. The proposed restoration method is composed by a three steps loop: regularize the image, fit the model parameters and update the regularization coefficient (by reweighting the fidelity term). To further demonstrate the efficiency of the proposed generic technique, two specific case studies involving structured PRNU and multi-capture compressive sensing are presented with simulation results.