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ECCV
1996
Springer
16 years 6 months ago
Dense Depth Map Reconstruction: A Minimization and Regularization Approach which Preserves Discontinuities
We present a variational approachto dense stereo reconstructionwhich combines powerful tools such as regularization and multi-scale processing to estimate directly depth from a num...
Luc Robert, Rachid Deriche
ICIP
2005
IEEE
16 years 6 months ago
An adaptive segmentation-based regularization term for image restoration
This paper proposes an original inhomogeneous restoration (deconvolution) model under the Bayesian framework. In this model, regularization is achieved, during the iterative resto...
Max Mignotte
SIGPRO
2010
154views more  SIGPRO 2010»
15 years 2 months ago
UPRE method for total variation parameter selection
Total Variation (TV) regularization is a popular method for solving a wide variety of inverse problems in image processing. In order to optimize the reconstructed image, it is imp...
Youzuo Lin, Brendt Wohlberg, Hongbin Guo
ECCV
2006
Springer
15 years 8 months ago
Wavelet-Based Super-Resolution Reconstruction: Theory and Algorithm
We present an analysis and algorithm for the problem of super-resolution imaging, that is the reconstruction of HR (high-resolution) images from a sequence of LR (lowresolution) im...
Hui Ji, Cornelia Fermüller
TMI
2008
116views more  TMI 2008»
15 years 4 months ago
Dynamic PET Reconstruction Using Wavelet Regularization With Adapted Basis Functions
Tomographic reconstruction from positron emission tomography (PET) data is an ill-posed problem that requires regularization. An attractive approach is to impose an 1-regularizatio...
J. Verhaeghe, Dimitri Van De Ville, I. Khalidov, Y...