0546240 20250123085732.220211005235959.9 85121685297 000819455102016 10.1109/ICIP42928.2021.9506502 5 s. P cav_un_epca*0546361978-1-6654-4115-52381-85491954-1958PiscatawayIEEE2021 blind deblurring SelfDeblur deep image prior cav_un_auth*0293863 Kotera Jan UTIA-B Zpracování obrazové informace Department of Image Processing ZOI ZOI Department of Image Processing CZ Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0101207 Šmídl Václav UTIA-B Adaptivní systémy Department of Adaptive Systems AS AS Department of Adaptive Systems Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0101209 Šroubek Filip UTIA-B Zpracování obrazové informace Department of Image Processing ZOI ZOI Department of Image Processing Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2021/ZOI/kotera-0546240.pdf GA20-27939S GA ČR cav_un_auth*0391986 The field of blind image deblurring was for a long time dominated by Maximum-A-Posteriori methods seeking the optimal pair of sharp image--blur of a suitable functional. Recently, learning-based methods, especially those based on deep convolutional neural networks, are proving effective and are receiving increasing attention by the research community. In 2020, Ren~et~al. proposed a deblurring method called SelfDeblur which combines the model-driven approach of traditional MAP methods and the generative power of neural nets. The method is capable of producing very high-quality results, yet it inherits some problems of MAP methods, especially possible convergence to a wrong local optimum. In this paper we propose several easy-to-implement modifications of SelfDeblur, namely suitable initialization, multiscale processing, and regularization, that improve the average performance of the original method and decrease the probability of failure. cav_un_auth*0414773 IEEE International Conference on Image Processing (ICIP) 2021 20210919 20210922 Anchorage US JD 20000 20200 20204 2022 3 PO RVO:67985556 http://hdl.handle.net/11104/0322888 S 2021 85121685297 SCOPUS PUBMED 000819455102016 WOS cav_un_epca*0546361 2021 IEEE International Conference on Image Processing : Proceedings IEEE 2021 Piscataway 1954 1958 978-1-6654-4115-5 2381-8549