0490175 20240103220111.520180610235959.9 85047017461 000434450200004 10.1109/LSP.2018.2836964 5 s. P cav_un_epca*02532121070-9908257 (2018)1024-1028Institute of Electrical and Electronics Engineers adaptive image prior image restoration variational Bayes cav_un_auth*0019204 Ševčík J. CZ cav_un_auth*0101207 Šmídl Václav Adaptivní systémy Department of Adaptive Systems AS AS UTIA-B Department of Adaptive Systems 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. http://library.utia.cas.cz/separaty/2018/AS/smidl-0490175.pdf cav_un_auth*0353427 LO1607 GA MŠk CZ cav_un_auth*0361425 GA18-05360S GA ČR Image restoration is typically defined as an ill-posed problem which has to be regularized to obtain an acceptable solution. In Bayesian interpretation, regularization is equivalent to prior model of the image. An added value of Bayesian point of view is the ability to form a hierarchical model and estimate the hyper-parameters of the prior from the data. Many prior models are available, usually based on automatic relevance determination principle applied to the transformed image. However, the transformation (the most common is a differential operator) is assumed to be known. In this paper, we propose to relax this assumption and estimate the image transformation from the data. The resulting algorithm is analytically tractable using the Variational Bayes method. Properties of the new prior are demonstrated on the problem of image super-resolution. WOS IN 10000 10200 10201 2019 3 4 A hod 4ah 20231122143229.6 RVO:67985556 http://hdl.handle.net/11104/0284543 1 Department of Adaptive Systems UTIA-B 10200 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS S 3+4 Article Engineering Electrical Electronic ENGINEERING.ELECTRICAL&ELECTRONIC 3.506 0.605 5.2 0.02494 1.037 11570 0.785 3.070 365 Q2 75.59 70.5 Q1 Q2 1.13 Q1 70.489 2018 Soubory v repozitáři: smidl-0490175.pdf 85047017461 SCOPUS PUBMED 000434450200004 WOS cav_un_epca*0253212 IEEE Signal Processing Letters 1070-9908 1558-2361 Roč. 25 č. 7 2018 1024 1028 Institute of Electrical and Electronics Engineers