Importance Sampling-Based Unscented Kalman Filter for Film-Grain Noise Removal

Autor:	A. N. Rajagopalan, Rangarajan Aravind, G.R.K. Sai Subrahmanyam
Rok vydání:	2008
Předmět:	Computer science business.industry Salt-and-pepper noise Kalman filter Agricultural products Canning Control theory Kalman filters Military data processing Nonlinear filtering Photographic films Wave filters Edge information Film-grain noise Importance sampling (IS) Non Gaussian noises Unscented Kalman filter (UKF) Gaussian noise (electronic) Computer Science Applications Extended Kalman filter symbols.namesake Noise Hardware and Architecture Gaussian noise Signal Processing Media Technology symbols Ensemble Kalman filter Computer vision Artificial intelligence Unscented transform business Algorithm Software Importance sampling
Zdroj:	IEEE Multimedia. 15:52-63
ISSN:	1070-986X
DOI:	10.1109/mmul.2008.32
Popis:	Photographic film contains film-grain noise that translates to multiplicative, non-Gaussian noise in the exposure domain. A method based on the unscented Kalman filter can suppress this noise while simultaneously preserving edge information. � 2008 IEEE.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::87bebd7fc464f972deed84a0fcabd031 https://doi.org/10.1109/mmul.2008.32 Zobrazit plný text záznamu