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On the Total Variation Dictionary Model
IEEE Transactions on Image Processing, 2010The goal of this paper is to provide a theoretical study of a total variation (TV) dictionary model. Based on the properties of convex analysis and bounded variation functions, the existence of solutions of the TV dictionary model is proved. We then show that the dual form of the model can be given by the minimization of the sum of the l(1) -norm of ...
Tieyong Zeng, Michael K. Ng 0001
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On the Total Variation of a Function
Canadian Mathematical Bulletin, 1981There are a number of theories which assign to a function defined on the real line a measure that reflects somehow the variation of that function. The most familiar of these is, of course, the Lebesgue-Stieltjes measure associated with any monotonie function.
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Total Cyclic Variation and Generalizations
Journal of Mathematical Imaging and Vision, 2012zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Daniel Cremers, Evgeny Strekalovskiy
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Anisotropic Total Variation Filtering
Applied Mathematics & Optimization, 2010zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Grasmair, Markus, Lenzen, Frank
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Total variation blind deconvolution
IEEE Transactions on Image Processing, 1998In this paper, we present a blind deconvolution algorithm based on the total variational (TV) minimization method proposed. The motivation for regularizing with the TV norm is that it is extremely effective for recovering edges of images as well as some blurring functions, e.g., motion blur and out-of-focus blur.
Tony F. Chan, Chiu-Kwong Wong
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Total Generalized Variation on a Tree
SIAM Journal on Imaging ScienceszbMATH Open Web Interface contents unavailable due to conflicting licenses.
Muhamed Kuric +2 more
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Decorrelated Vectorial Total Variation
2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014This paper proposes a new vectorial total variation prior (VTV) for color images. Different from existing VTVs, our VTV, named the decorrelated vectorial total variation prior (D-VTV), measures the discrete gradients of the luminance component and that of the chrominance one in a separated manner, which significantly reduces undesirable uneven color ...
Shunsuke Ono, Isao Yamada
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2010 IEEE International Conference on Image Processing, 2010
We propose total subset variation (TSV), a convexity preserving generalization of the total variation (TV) prior, for higher order clique MRF. A proposed differentiable approximation of the TSV prior makes it amenable for use in large images (e.g. 1080p).
Sanjeev Kumar 0003, Truong Q. Nguyen
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We propose total subset variation (TSV), a convexity preserving generalization of the total variation (TV) prior, for higher order clique MRF. A proposed differentiable approximation of the TSV prior makes it amenable for use in large images (e.g. 1080p).
Sanjeev Kumar 0003, Truong Q. Nguyen
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Multiscale Modeling & Simulation, 2007
In this paper we analyze iterative regularization with the Bregman distance of the total variation seminorm. Moreover, we prove existence of a solution of the corresponding flow equation as introduced in [M. Burger, G. Gilboa, S. Osher, and J. Xu, Commun. Math. Sci., 4 (2006), pp.
Martin Burger 0001 +3 more
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In this paper we analyze iterative regularization with the Bregman distance of the total variation seminorm. Moreover, we prove existence of a solution of the corresponding flow equation as introduced in [M. Burger, G. Gilboa, S. Osher, and J. Xu, Commun. Math. Sci., 4 (2006), pp.
Martin Burger 0001 +3 more
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Total Nuclear Variation and Jacobian Extensions of Total Variation for Vector Fields
IEEE Transactions on Image Processing, 2014We explore a class of vectorial total variation (VTV) measures formed as the spatial sum of a pixel-wise matrix norm of the Jacobian of a vector field. We give a theoretical treatment that indicates that, while color smearing and affine-coupling bias (often reported as gray-scale bias) are typically cited as drawbacks for VTV, these are actually ...
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