International audienceBecause they are based on finite differences, usual discretizations of the Total Variation lead to aliased images. We propose a new discretization called spectral total variation that agrees with Shannon sampling principles and produces images that can be exactly interpolated. The quality improvement is illustrated experimentally in the case of image deblurring
The main aim of this paper is to study total variation (TV) regularization in deblurring and sparse ...
Abstract. We propose a variational model which permits to simultaneously de-blur and oversample an i...
Recently, a fast alternating minimization algorithm for total variation image deblurring (FTVd) has ...
Because they are based on finite differences, usual discretizations of the Total Variation lead to a...
Discretization schemes commonly used for total variation regularization lead to images that are diff...
International audienceResolution enhancement of digital images may be seen has a ill-posed inverse p...
These notes address various theoretical and practical topics related to Total Variation based image ...
We summarize in this lectures some of our results about the Min-imizing Total Variation Flow, which ...
In this paper, we define the necessity for recourse to Total Variation method in digital image filte...
Denoising is the problem of removing the inherent noise from an image. The standard noise model is a...
We show two ways to combine wavelet packets and total variation based deblurring methods. For this p...
International audienceThe total generalized variation extends the total variation by incorporating h...
The minimization of the total variation is an important tool of image processing. A lot of authors h...
In this digital age, it is more important than ever to have good methods for processing images. We f...
The widely used Total Variation de-noising algorithm can preserve sharp edge, while removing noise. ...
The main aim of this paper is to study total variation (TV) regularization in deblurring and sparse ...
Abstract. We propose a variational model which permits to simultaneously de-blur and oversample an i...
Recently, a fast alternating minimization algorithm for total variation image deblurring (FTVd) has ...
Because they are based on finite differences, usual discretizations of the Total Variation lead to a...
Discretization schemes commonly used for total variation regularization lead to images that are diff...
International audienceResolution enhancement of digital images may be seen has a ill-posed inverse p...
These notes address various theoretical and practical topics related to Total Variation based image ...
We summarize in this lectures some of our results about the Min-imizing Total Variation Flow, which ...
In this paper, we define the necessity for recourse to Total Variation method in digital image filte...
Denoising is the problem of removing the inherent noise from an image. The standard noise model is a...
We show two ways to combine wavelet packets and total variation based deblurring methods. For this p...
International audienceThe total generalized variation extends the total variation by incorporating h...
The minimization of the total variation is an important tool of image processing. A lot of authors h...
In this digital age, it is more important than ever to have good methods for processing images. We f...
The widely used Total Variation de-noising algorithm can preserve sharp edge, while removing noise. ...
The main aim of this paper is to study total variation (TV) regularization in deblurring and sparse ...
Abstract. We propose a variational model which permits to simultaneously de-blur and oversample an i...
Recently, a fast alternating minimization algorithm for total variation image deblurring (FTVd) has ...
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