Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Thomas Debarre"'
Publikováno v:
IEEE Open Journal of Signal Processing, Vol 3, Pp 140-154 (2022)
Beside the minimizationof the prediction error, two of the most desirable properties of a regression scheme are stability and interpretability. Driven by these principles, we propose continuous-domain formulations for one-dimensional regression probl
Externí odkaz:
https://doaj.org/article/b043d97a15884de3a83a31dda3ab1db0
Publikováno v:
IEEE Open Journal of Signal Processing, Vol 2, Pp 545-558 (2021)
We present a novel framework for the reconstruction of 1D composite signals assumed to be a mixture of two additive components, one sparse and the other smooth, given a finite number of linear measurements. We formulate the reconstruction problem as
Externí odkaz:
https://doaj.org/article/1c7cf37aba1449319c293363c48855cc
Beside the minimization of the prediction error, two of the most desirable properties of a regression scheme are stability and interpretability. Driven by these principles, we propose continuous-domain formulations for one-dimensional regression prob
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e669a7d2562cd34b9409eff735cf8a91
http://arxiv.org/abs/2112.13542
http://arxiv.org/abs/2112.13542
Publikováno v:
IEEE Transactions on Signal Processing
We study one-dimensional continuous-domain inverse problems with multiple generalized total-variation regularization, which involves the joint use of several regularization operators. Our starting point is a new representer theorem that states that s
This paper studies the continuous-domain inverse problem of recovering Radon measures on the one-dimensional torus from low-frequency Fourier coefficients, where Kc is the cutoff frequency. Our approach consists in minimizing the total-variation norm
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::39431f30d6042bbec3e662f1caa811c1
http://arxiv.org/abs/2009.11855
http://arxiv.org/abs/2009.11855
Publikováno v:
ISBI
Scanning transmission X-ray microscopy (STXM) produces images in which each pixel value is related to the measured attenuation of an X-ray beam. In practice, the location of the illuminated region does not exactly match the desired uniform pixel grid
Autor:
Daniel Sage, Emmanuel Soubies, Michael Unser, Thanh-an Pham, Thomas Debarre, Ferréol Soulez, Michael T. McCann, Laurène Donati
Publikováno v:
Inverse Problems
Inverse Problems, 2019, 35 (10), pp.104006. ⟨10.1088/1361-6420/ab2ae9⟩
Inverse Problems, IOP Publishing, 2019, 35 (10), pp.104006. ⟨10.1088/1361-6420/ab2ae9⟩
Inverse Problems, 2019, 35 (10), pp.104006. ⟨10.1088/1361-6420/ab2ae9⟩
Inverse Problems, IOP Publishing, 2019, 35 (10), pp.104006. ⟨10.1088/1361-6420/ab2ae9⟩
GlobalBioIm is an open-source MATLAB® library for solving inverse problems. The library capitalizes on the strong commonalities between forward models to standardize the resolution of a wide range of imaging inverse problems. Endowed with an operato
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::aede440b51000e04c27702783768f7f4
Publikováno v:
IEEE Transactions on Information Theory
We study continuous-domain linear inverse problems with generalized total-variation (gTV) regularization, expressed in terms of a regularization operator L. It has recently been proved that such inverse problems have sparse spline solutions, with few
Autor:
Emmanuel Soubies, Ferréol Soulez, Michael T McCann, Thanh-an Pham, Laurène Donati, Thomas Debarre, Daniel Sage, Michael Unser
Publikováno v:
Inverse Problems; Oct2019, Vol. 35 Issue 10, p1-1, 1p
Publikováno v:
ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
ICASSP
ICASSP
We propose a discretization method for continuous-domain linear inverse problems with multiple-order total-variation (TV) regularization. It is based on a recent result that proves that such inverse problems have sparse polynomial-spline solutions. O
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::221baf1ee2e7e5910b02755981a57afa