0000000000400164
AUTHOR
Luminita A. Vese
showing 2 related works from this author
Multiframe image restoration in the presence of noisy blur kernel
2009
We wish to recover an original image u from several blurry-noisy versions f k , called frames. We assume a more severe degradation model, in which the image u has been blurred by a noisy (stochastic) point spread function. We consider the problem of restoring the degraded image in a variational framework. Since the recovery of u from one single frame f is a highly ill-posed problem, we formulate two minimization problems based on the multiframe approach proposed for image super-resolution by Marquina-Osher [13]. Several experimental results for image restoration are shown, illustrating that the proposed models give visually satisfactory results.
Variational multiframe restoration of images degraded by noisy (stochastic) blur kernels
2013
This article introduces and explores a class of degradation models in which an image is blurred by a noisy (stochastic) point spread function (PSF). The aim is to restore a sharper and cleaner image from the degraded one. Due to the highly ill-posed nature of the problem, we propose to recover the image given a sequence of several observed degraded images or multiframes. Thus we adopt the idea of the multiframe approach introduced for image super-resolution, which reduces distortions appearing in the degraded images. Moreover, we formulate variational minimization problems with the robust (local or nonlocal) L^1 edge-preserving regularizing energy functionals, unlike prior works dealing wit…