Nonlinear total variation based noise removal algorithms
Proceedings of the eleventh annual international conference of the Center for Nonlinear Studies on Experimental mathematics : computational issues in nonlinear science: computational issues in nonlinear science
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
Fast texture synthesis using tree-structured vector quantization
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
Oscillating Patterns in Image Processing and Nonlinear Evolution Equations: The Fifteenth Dean Jacqueline B. Lewis Memorial Lectures
Texture Synthesis by Non-Parametric Sampling
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
An Algorithm for Total Variation Minimization and Applications
Journal of Mathematical Imaging and Vision
A Variational Approach to Remove Outliers and Impulse Noise
Journal of Mathematical Imaging and Vision
Image Decomposition into a Bounded Variation Component and an Oscillating Component
Journal of Mathematical Imaging and Vision
Image completion with structure propagation
ACM SIGGRAPH 2005 Papers
Structure-Texture Image Decomposition--Modeling, Algorithms, and Parameter Selection
International Journal of Computer Vision
Fast Anisotropic Smoothing of Multi-Valued Images using Curvature-Preserving PDE's
International Journal of Computer Vision
Constrained and SNR-Based Solutions for TV-Hilbert Space Image Denoising
Journal of Mathematical Imaging and Vision
Fast Image Inpainting Based on Coherence Transport
Journal of Mathematical Imaging and Vision
Inpainting and Zooming Using Sparse Representations
The Computer Journal
Some First-Order Algorithms for Total Variation Based Image Restoration
Journal of Mathematical Imaging and Vision
Disocclusion: a variational approach using level lines
IEEE Transactions on Image Processing
Simultaneous structure and texture image inpainting
IEEE Transactions on Image Processing
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This article presents a new adaptive texture model. Locally parallel oscillating patterns are modeled with a weighted Hilbert space defined over local Fourier coefficients. The weights on the local Fourier atoms are optimized to match the local orientation and frequency of the texture. We propose an adaptive method to decompose an image into a cartoon layer and a locally parallel texture layer using this model and a total variation cartoon model. This decomposition method is then used to denoise an image containing oscillating patterns. Finally we show how to take advantage of such a separation framework to simultaneously inpaint the structure and texture components of an image with missing parts. Numerical results show that our method improves state of the art algorithms for directional and complex textures.