A Convex Approach for Variational Super-Resolution

We propose a convex variational framework to compute high resolution images from a low resolution video. The image formation process is analyzed to provide to a well designed model for warping, blurring, downsampling and regularization. We provide a comprehensive investigation of the single model components. The super-resolution problem is modeled as a minimization problem in an unified convex framework, which is solved by a fast primal dual algorithm. A comprehensive evaluation on the influence of different kinds of noise is carried out. The proposed algorithm shows excellent recovery of information for various real and synthetic datasets.

• Type: Journal
• Year: 2010
• Where: DAGM
• Authors: Markus Unger, Thomas Pock, Manuel Werlberger, Horst Bischof
• Keywords: Convex Variational Framework, DAGM 2010, Image Processing, Low Resolution Video, Unified Convex Framework