0446068 20240103210319.720150806235959.9 84960892963 000380472300003 10.1109/ICCIS.2015.7274540 6 s. E cav_un_epca*0446067978-1-4673-7337-1CIS13-18445 Hoes Lane, Piscataway, NJ 08854, USAIEEE2015 Texture restoration Gaussian mixture model cav_un_auth*0101093 Rozpoznávání obrazu Department of Pattern Recognition RO RO Department of Pattern Recognition Haindl Michal UTIA-B Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0101100 Rozpoznávání obrazu Department of Pattern Recognition RO RO Department of Pattern Recognition Havlíček Vojtěch UTIA-B Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2015/RO/haindl-0446068.pdf cav_un_auth*0303439 GA14-10911S GA ČR CZ Visual texture restoration strives not necessarily to recover the exact pixel-wise correspondence with some original unobservable texture but rather a texture which is visually indiscernible from the original one. This differs from the standard image restoration objective so it can consequently lead to different restoration techniques. A novel multispectral texture restoration method, capable to reduce simultaneously additive noise and to restore missing textural parts is presented. The restoration method is based on a descriptive, unusually complex, three-dimensional, spatial Gaussian mixture model. The model is inherently multispectral thus it does not suffer with the spectral quality compromises of the most alternative approaches. cav_un_auth*0318307 7th IEEE International Conferences on Cybernetics and Intelligent Systems (CIS), and Robotics, Automation and Mechatronics (RAM) 17.07.2015-17.07.2015 Siem Reap KH BD 2016 2 PR RVO:67985556 http://hdl.handle.net/11104/0248313 S 2015 84960892963 SCOPUS 000380472300003 WOS cav_un_epca*0446067 IEEE 7th International Conferences on Cybernetics and Intelligent Systems (CIS), and Robotics, Automation and Mechatronics (RAM) CIS 978-1-4673-7337-1 13 18 445 Hoes Lane, Piscataway, NJ 08854, USA IEEE 2015