Abstract. The paper presents an unsupervised method for partiallyblurred image restoration without influencing unblurred regions or objects. Maximum a posteriori estimation of para...
We consider the problem of deblurring images which have been blurred by different reasons during image acquisition. We propose a variational approach admitting spatially variant an...
This paper proposes a novel sparse representation model called centralized sparse representation (CSR) for image restoration tasks. In order for faithful image reconstruction, it ...
We propose a deblurring algorithm that explicitly takes into account the sparse characteristics of natural images and does not entail solving a numerically ill-conditioned backwar...
The satellite image deconvolution problem is ill-posed and must be regularized. Herein, we use an edge-preserving regularization model using a ' function, involving two hyper...