DocumentCode :
3257966
Title :
A novel model using Kalman filtering for image restoration
Author :
Liu, Zhen ; Dong, Fangfang ; Xie, Zheng ; Bai, Yongqiang
Author_Institution :
Dept. of Math., Zhejiang Univ. of Technol., Hangzhou, China
Volume :
2
fYear :
2010
fDate :
16-18 Oct. 2010
Firstpage :
811
Lastpage :
815
Abstract :
A novel Kalman filtering model and algorithm is proposed in the paper. We give the state equation from the Euler-Lagrange equation of the total variation model. The nonlinear partial differential equation is added with a gaussian white noise and discretized by finite difference method. Then the parameters of the state equation can be derived from the discrete equation directly. We also discuss some numerical experiments which prove our proposed model and algorithm to be more efficient.
Keywords :
Gaussian noise; Kalman filters; finite difference methods; image restoration; partial differential equations; white noise; Euler-Lagrange equation; Gaussian white noise; Kalman filtering; discrete equation; finite difference method; image restoration; nonlinear partial differential equation; state equation; total variation model; Equations; Image edge detection; Image restoration; Kalman filters; Mathematical model; Noise; Pixel;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image and Signal Processing (CISP), 2010 3rd International Congress on
Conference_Location :
Yantai
Print_ISBN :
978-1-4244-6513-2
Type :
conf
DOI :
10.1109/CISP.2010.5646847
Filename :
5646847
Link To Document :
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