Signal-Dependent Film Grain Noise Removal and Based on Higher- Order Statistics Generation
Jacky Chun, Kit Yan, Dimitrios Hatzinakos · 1997
In this paper, we propose a new noise filtering scheme that is based on higher-order statistics (H. OS.) for photographic images corrupted by signal-dependent film grain noise. In addition, reliable estimation of the noise parameter using H.O.S. is proposed. This parameter estimation technique can be used to generate film grain noise which has applications in motion picture and television productions. Simulation results show that the proposed filter perform better than existing methods which are based on second-order statistics.