Title :
Signal-dependent film grain noise removal and generation based on higher-order statistics
Author :
Yan, Jacky Chun Kit ; Hatzinakos, Dimitrios
Author_Institution :
Dept. of Electr. & Comput. Eng., Toronto Univ., Ont., Canada
Abstract :
In this paper, we propose a new noise filtering scheme that is based on higher-order statistics (HOS) for photographic images corrupted by signal-dependent film grain noise. In addition, reliable estimation of the noise parameter using HOS 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
Keywords :
Gaussian noise; Wiener filters; higher order statistics; image processing; parameter estimation; photography; Wiener type filter; higher-order statistics; motion picture productions; noise filtering scheme; noise parameter estimation; photographic images; signal-dependent film grain noise generation; signal-dependent film grain noise removal; simulation; television productions; Additive noise; Filtering; Finite impulse response filter; Gaussian noise; Higher order statistics; Motion pictures; Noise generators; Noise measurement; Signal generators; Wiener filter;
Conference_Titel :
Higher-Order Statistics, 1997., Proceedings of the IEEE Signal Processing Workshop on
Conference_Location :
Banff, Alta.
Print_ISBN :
0-8186-8005-9
DOI :
10.1109/HOST.1997.613491
