0474520 20240103214042.420170511235959.9 85019073923 000406771300048 10.1109/ICPR.2016.7899645 6 s. P cav_un_epca*0467540978-1-5090-4846-5271-276PiscatawayIEEE2016 Image coding Image restoration JPEG cav_un_auth*0108377 Šorel Michal Zpracování obrazové informace Department of Image Processing ZOI ZOI UTIA-B Department of Image Processing Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0312355 Bartoš Michal Zpracování obrazové informace Department of Image Processing ZOI ZOI UTIA-B Department of Image Processing CZ Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2017/ZOI/sorel-0474520.pdf cav_un_auth*0338628 GA16-13830S GA ČR CZ Standard decompression of JPEG images produces artifacts along edges and a disturbing checkerboard pattern. To reduce these artifacts, decompression can be formulated as an image reconstruction problem within Bayesian maximum a posteriori probability framework. In this type of problem, the prior information about an image is typically given by the l1 norm of its sparse domain representation. In this paper, we show how the solution of this problem can be achieved very efficiently using the alternating direction method of multipliers if the sparsity domain forms a tight frame. The proposed algorithm restores images without disturbing JPEG artifacts in several iterations, typically considerably less than competing algorithms. The quality of reconstruction both visually and in terms of SNR primarily depends on the tight frame used. cav_un_auth*0340495 23rd International Conference on Pattern Recognition ICPR 2016 20161204 20161208 Cancún MX JD 10000 10200 10201 2018 2 PR RVO:67985556 http://hdl.handle.net/11104/0271768 S n.a. Proceedings Paper Computer Science Artificial Intelligence 2016 85019073923 SCOPUS PUBMED 000406771300048 WOS cav_un_epca*0467540 Proceedings of the 23rd International Conference on Pattern Recognition (ICPR) 978-1-5090-4846-5 271 276 Piscataway IEEE 2016