Dual Norms and Image Decomposition Models
International Journal of Computer Vision
Adapted Total Variation for Artifact Free Decompression of JPEG Images
Journal of Mathematical Imaging and Vision
Structure-Texture Image Decomposition--Modeling, Algorithms, and Parameter Selection
International Journal of Computer Vision
Image Deblurring in the Presence of Impulsive Noise
International Journal of Computer Vision
Image Compression Through a Projection onto a Polyhedral Set
Journal of Mathematical Imaging and Vision
A Truncated Lagrange Method for Total Variation-Based Image Restoration
Journal of Mathematical Imaging and Vision
A Nonlinear Multigrid Method for Total Variation Minimization from Image Restoration
Journal of Scientific Computing
Multiplicative Noise Removal Using L1 Fidelity on Frame Coefficients
Journal of Mathematical Imaging and Vision
Super-resolution using sub-band constrained total variation
SSVM'07 Proceedings of the 1st international conference on Scale space and variational methods in computer vision
On the total variation dictionary model
IEEE Transactions on Image Processing
Deconvolving Poissonian images by a novel hybrid variational model
Journal of Visual Communication and Image Representation
An adaptive variational model for image decomposition
EMMCVPR'05 Proceedings of the 5th international conference on Energy Minimization Methods in Computer Vision and Pattern Recognition
Constrained total variation minimization and application in computerized tomography
EMMCVPR'05 Proceedings of the 5th international conference on Energy Minimization Methods in Computer Vision and Pattern Recognition
Image deblurring in the presence of salt-and-pepper noise
Scale-Space'05 Proceedings of the 5th international conference on Scale Space and PDE Methods in Computer Vision
Denoising of audio data by nonlinear diffusion
Scale-Space'05 Proceedings of the 5th international conference on Scale Space and PDE Methods in Computer Vision
Structure-Texture decomposition by a TV-Gabor model
VLSM'05 Proceedings of the Third international conference on Variational, Geometric, and Level Set Methods in Computer Vision
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We present a general framework for image restoration; despite its simplicity, certain variational and certain wavelet approaches can be formulated within this framework. This permits the construction of a natural model, with only one parameter, which has the advantages of both approaches. We give a mathematical analysis of this model, describe our algorithm and illustrate this by some experiments.