In this paper the blind deconvolution problem is formulated using the variational framework. With its use approximations of the involved probability distributions are developed re...
Javier Mateos, Rafael Molina, Aggelos K. Katsaggel...
In this paper, we introduce a novel approach for simultaneous restoration and segmentation of blurred, noisy images by approaching a variant of the Mumford-Shah functional from a ...
Traditional nonlinear filtering techniques are observed in underutilization of blur identification techniques, and vice versa. To improve blind image restoration, a designed edg...
We present a new Coprime Blurred Pair (CBP) theory that may benefit a number of computer vision applications. A CBP is constructed by blurring the same latent image with two unkn...
We address the problem of space-variant image deblurring, where different parts of the image are blurred by different blur kernels. Assuming a region-wise space variant point spr...