Multi-Frame Super-Resolution
14 papers with code • 1 benchmarks • 3 datasets
When multiple images of the same view are taken from slightly different positions, perhaps also at different times, then they collectively contain more information than any single image on its own. Multi-Frame Super-Resolution fuses these low-res inputs into a composite high-res image that can reveal some of the original detail that cannot be recovered from any low-res image alone.
( Credit: HighRes-net )
BurstSR
Inter4K
PROBA-V
Latest papers with no code
Private Eye: On the Limits of Textual Screen Peeking via Eyeglass Reflections in Video Conferencing
Our models and experimental results in a controlled lab setting show it is possible to reconstruct and recognize with over 75% accuracy on-screen texts that have heights as small as 10 mm with a 720p webcam.
Multi-frame Super-resolution from Noisy Data
Obtaining high resolution images from low resolution data with clipped noise is algorithmically challenging due to the ill-posed nature of the problem.
Parallax estimation for push-frame satellite imagery: application to super-resolution and 3D surface modeling from Skysat products
Recent constellations of satellites, including the Skysat constellation, are able to acquire bursts of images.
Joint Super-Resolution and Rectification for Solar Cell Inspection
Visual inspection of solar modules is an important monitoring facility in photovoltaic power plants.
Multi-Frame Super-Resolution Combining Demons Registration and Regularized Bayesian Reconstruction
This letter proposes a multi-frame super-resolution framework by combining Demons registration with Bayesian-based regularized reconstruction.
Video Face Super-Resolution with Motion-Adaptive Feedback Cell
Current state-of-the-art CNN methods usually treat the VSR problem as a large number of separate multi-frame super-resolution tasks, at which a batch of low resolution (LR) frames is utilized to generate a single high resolution (HR) frame, and running a slide window to select LR frames over the entire video would obtain a series of HR frames.
Multi-Frame Super-Resolution Reconstruction with Applications to Medical Imaging
The optical resolution of a digital camera is one of its most crucial parameters with broad relevance for consumer electronics, surveillance systems, remote sensing, or medical imaging.
Frame-Recurrent Video Super-Resolution
Recent advances in video super-resolution have shown that convolutional neural networks combined with motion compensation are able to merge information from multiple low-resolution (LR) frames to generate high-quality images.
A Nuclear-norm Model for Multi-Frame Super-Resolution Reconstruction from Video Clips
Then a low-rank model is used to construct the reference frame in high-resolution by incorporating the information of the low-resolution frames.
Light Field Super-Resolution Via Graph-Based Regularization
We adopt a multi-frame alike super-resolution approach, where the complementary information in the different light field views is used to augment the spatial resolution of the whole light field.
