Spatial Super Resolution (SR) aims to recover fine image details, smaller than a pixel size. Temporal SR aims to recover rapid dynamic events that occur faster than the video fra...
A regression model in the tensorPCA subspace is proposed in this paper for face super-resolution reconstruction. An approximate conditional probability model is used for the tenso...
The choice of the over-complete dictionary that sparsely represents data is of prime importance for sparse codingbased image super-resolution. Sparse coding is a typical unsupervi...
A fast super-resolution reconstruction algorithm designed for license plate recognition is proposed in this paper. It uses a new reduced cost function to produce images of higher ...
The problem of recovering a high-resolution image from a set of distorted (e.g., warped, blurred, noisy) and low-resolution images is known as super-resolution. Accurate motion est...