Scale-Space and Edge Detection Using Anisotropic Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Super-Resolution Imaging
Limits on Super-Resolution and How to Break Them
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
Fundamental Limits of Reconstruction-Based Superresolution Algorithms under Local Translation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Lucas/Kanade meets Horn/Schunck: combining local and global optic flow methods
International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Simultaneous inpainting and motion estimation of highly degraded video-sequences
SCIA'03 Proceedings of the 13th Scandinavian conference on Image analysis
Extraction of high-resolution frames from video sequences
IEEE Transactions on Image Processing
Fast and robust multiframe super resolution
IEEE Transactions on Image Processing
Variational optical flow computation in real time
IEEE Transactions on Image Processing
A Scale-Space Approach to Landmark Constrained Image Registration
SSVM '09 Proceedings of the Second International Conference on Scale Space and Variational Methods in Computer Vision
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In this paper we present a variational, spatiotemporal video super resolution scheme that produces not just one but n high resolution video frames from an n frame low resolution video sequence. We use a generic prior and the output is artifact-free, sharp and superior in quality to state of the art home cinema video processors. Unlike many other super resolution schemes, ours does not limit itself to just translational or affine motion, or to certain subclasses of image content to optimize the output quality.We present a link between image reconstruction and super resolution and formulate our super resolution constraint with arbitrary up-scaling factors in space from that.