0360217 20240903170622.920110707235959.9 000293207900009 16 s. cav_un_epca*02971630023-5954473 (2011)439-454Ústav teorie informace a automatizace AV ČR, v. v. i. image restoration blind deconvolution deblurring 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*0101209 Šroubek Filip 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*0101087 Flusser Jan 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. http://library.utia.cas.cz/separaty/2011/ZOI/sorel-0360217.pdf 1M0572 GA MŠk cav_un_auth*0001814 CEZ:AV0Z10750506 Blur is a common problem that limits the effective resolution of many imaging systems. In this article, we give a general overview of methods that can be used to reduce the blur. This includes the classical multi-channel deconvolution problems as well as challenging extensions to spatially varying blur. The proposed methods are formulated as energy minimization problems with specific regularization terms on images and blurs. Experiments on real data illustrate very good and stable performance of the methods. 2012 JD 4 A O 4a 4o 20231122134557.0 http://hdl.handle.net/11104/0197820 COMPUTERSCIENCECYBERNETICS 0.473 0.033 9.5 0.0016 0.277 403 61 21 0.307 20.45 0.61 Q2 23.915 17.500 Q4 Q3 2011 Soubory v repozitáři: sorel-0360217.pdf, 0360217.pdf 000293207900009 WOS cav_un_epca*0297163 Kybernetika 0023-5954 Roč. 47 č. 3 2011 439 454 Ústav teorie informace a automatizace AV ČR, v. v. i.