Partial differential equations (PDEs) have been successfully applied to many computer vision and image processing problems. However, designing PDEs requires high mathematical skill...
The two main plagues of image restoration are oscillations and smoothing. Traditional image restoration techniques prevent parasitic oscillations by resorting to smooth regulariza...
Regularization constraints are necessary in inverse problems such as image restoration, optical flow computation or shape from shading to avoid the singularities in the solution....
In traditional digital image restoration, the blurring process of the optic is assumed known. Many previous research efforts have been trying to reconstruct the degraded image or ...
In image restoration tasks, a heavy-tailed gradient distribution of natural images has been extensively exploited as an image prior. Most image restoration algorithms impose a spa...
Taeg Sang Cho, Neel Joshi, Larry Zitnick, Sing Bin...
We wish to recover an original image u from several blurry-noisy versions fk, called frames. We assume a more severe degradation model, in which the image u has been blurred by a ...
This paper deals with a view interpolation problem using multiple images captured with a circular camera array. A novel deconvolution method for reconstructing a virtual image at ...
Image restoration is a keen problem of low level vision. In this paper, we propose a novel - assumption-free on the noise model - technique based on random walks for image enhancem...
In this paper, we present a new approach for image labeling based on the recently introduced graph-shifts algorithm. Graph-shifts is an energy minimization algorithm that does lab...
We propose in this paper to unify two different ap-
proaches to image restoration: On the one hand, learning a
basis set (dictionary) adapted to sparse signal descriptions
has p...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...