Texture Synthesis by Non-Parametric Sampling
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Space-Time Adaptation for Patch-Based Image Sequence Restoration
IEEE Transactions on Pattern Analysis and Machine Intelligence
Nonlocal Image and Movie Denoising
International Journal of Computer Vision
Efficient object-based video inpainting
Pattern Recognition Letters
Generalizing the Nonlocal-means to super-resolution reconstruction
IEEE Transactions on Image Processing
Nonlocal Discrete Regularization on Weighted Graphs: A Framework for Image and Manifold Processing
IEEE Transactions on Image Processing
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We present nonlocal algorithms for video denoising, simplification and inpainting based on a generic framework of discrete regularization on graphs. We express video denoising, simplification and inpainting problems using the same variational formulation. The main advantage of this framework is the unification of local and nonlocal approaches for these processing procedures. We take advantage of temporal and spatial redundancies in order to produce high quality results. In this paper, we consider a video sequence as a volume rather than a sequence of frames, and employ algorithms that do not require any motion estimation. For video inpainting, we unify geometric- and texture-synthesis-based approaches. To reduce the computational effort, we propose an optimized method that is faster than the nonlocal approach, while producing equally appealing results.