Restoration and zoom of irregularly sampled, blurred, and noisy images by accurate total variation minimization with local constraints

We propose an algorithm to solve a problem in image restoration which considers several different aspects of it, namely irregular sampling, denoising, deconvolution, and zooming. Our algorithm is based on an extension of a previous image denoising algorithm proposed by A. Chambolle using total variation, combined with irregular to regular sampling algorithms proposed by H. G. Feichtinger, K. Grochenig, M. Rauth, and T. Strohmer. Finally, we present some experimental results and compare them with those obtained with the algorithm proposed by K. Grochenig et al.