• Aucun résultat trouvé

On the amount of regularization for super-resolution reconstruction

N/A
N/A
Protected

Academic year: 2021

Partager "On the amount of regularization for super-resolution reconstruction"

Copied!
12
0
0

Texte intégral

Figure

Fig. 2. Validity of the assumption of commutativity: (a) HR image (b) Blurred HR image (c) image reconstructed from 16 LR images with M = 2 by neglecting the blur
Fig. 4. Convergence of the estimator N 1 A H w. Interpolation error with respect to the number of LR images.
Fig. 5. A real regularization free super-resolution (a) (b) Low resolution image for experiments 1 and 2, (c) (d) reference images (ground truth + noise) (e) (f) images reconstructed without regularization.
Fig. 6. Local conditioning of the SR problem. (a) Zoom on the fusion of the 4 LR grids (60 × 60 pixels upper left corner)
+4

Références

Documents relatifs

It is expected that the result is not true with = 0 as soon as the degree of α is ≥ 3, which means that it is expected no real algebraic number of degree at least 3 is

First introduced by Faddeev and Kashaev [7, 9], the quantum dilogarithm G b (x) and its variants S b (x) and g b (x) play a crucial role in the study of positive representations

On the other hand, for reconstructing the frequency spectrum or the time signal of prelocalized sources, the regularization term has to reflect prior information on the nature of

The underlying idea behind this regularization strategy was to combine the advantages of the iterated Tikhonov regularization, which can be thought as an iterative refinement of

In particular, the practical interest of updating the regularization parameter during the identification process has been pointed out, as well as the relative performances of

A distribution-wise GP model is a model with improved interpolation properties at redundant points: the trajectories pass through data points that are uniquely defined

[r]

It can be seen as an extension to the space-time domain of the Proper Generalized Decomposition (PGD) method previously proposed in DIC [6] where the dimensions of space were