Title :
Importance Sampling-Based Unscented Kalman Filter for Film-Grain Noise Removal
Author :
Subrahmanyam, G. R K Sai ; Rajagopalan, A.N. ; Aravind, Rangarajan
Author_Institution :
Indian Inst. of Technol. Madras, Madras
Abstract :
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.
Keywords :
Kalman filters; image denoising; image sampling; photography; edge information preservation; film-grain noise removal; importance sampling; noise suppression; nonGaussian noise; photographic film; unscented Kalman filter; Additive white noise; Degradation; Equations; Industrial relations; Layout; Monte Carlo methods; Motion pictures; Noise measurement; Noise reduction; Silver; Markov random field (MRF); discontinuity adaptive MRFs; film-grain noise; importance sampling; unscented Kalman filter;
Journal_Title :
MultiMedia, IEEE
DOI :
10.1109/MMUL.2008.32
