CORR
2012
Springer
12 years 1 days ago
2012
Springer
Suppose that we observe noisy linear measurements of an unknown signal that can be modeled as the sum of two component signals, each of which arises from a nonlinear sub-manifold ...
CORR
2011
Springer
12 years 7 months ago
2011
Springer
Statistical dependencies among wavelet coefficients are commonly represented by graphical models such as hidden Markov trees (HMTs). However, in linear inverse problems such as d...
ICIP
2009
IEEE
14 years 5 months ago
2009
IEEE
This work focuses on several optimization problems involved in recovery of sparse solutions of linear inverse problems. Such problems appear in many fields including image and sig...
ICIP
2006
IEEE
14 years 6 months ago
2006
IEEE
Recent studies in linear inverse problems have recognized the sparse representation of unknown signal in a certain basis as an useful and effective prior information to solve thos...
ECCV
2008
Springer
14 years 6 months ago
2008
Springer
This article proposes a new framework to regularize linear inverse problems using the total variation on non-local graphs. This nonlocal graph allows to adapt the penalization to t...
ICCV
2005
IEEE
14 years 6 months ago
2005
IEEE
The goal of deconvolution is to recover an image x from its convolution with a known blurring function. This is equivalent to inverting the linear system y = Hx. In this paper we ...
CVPR
2008
IEEE
14 years 6 months ago
2008
IEEE
Linear inverse problems in computer vision, including motion estimation, shape fitting and image reconstruction, give rise to parameter estimation problems with highly correlated ...