Artifact-Free JPEG Decompression with Total Generalized Variation

Kristian Bredies, Martin Holler
Institute of Mathematics and Scientific Computing, Karl-Franzens University Graz, Heinrichstrasse 36, 8010 Graz, Austria
International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAPP 2012), SFB-Report 2011-029, 2012



   author={Bredies, K. and Holler, M.},



Download Download (PDF)   View View   Source Source   



We propose a new model for the improved reconstruction of JPEG (Joint Photographic Experts Group) images. Given a JPEG compressed image, our method first determines the set of possible source images and then specifically chooses one of these source images satisfying additional regularity properties. This is realized by employing the recently introduced Total Generalized Variation (TGV) as regularization term and solving a constrained minimization problem. In order to obtain an optimal solution numerically, we propose a primaldual algorithm. We have developed a parallel implementation of this algorithm for the CPU and the GPU, using OpenMP and Nvidia’s Cuda, respectively. Finally, experiments have been performed, confirming a good visual reconstruction quality as well as the suitability for real-time application.
No votes yet.
Please wait...

* * *

* * *

HGPU group © 2010-2021 hgpu.org

All rights belong to the respective authors

Contact us: