DocumentCode :
456743
Title :
A New Hybrid PDE Denoising Model Based on Markov Random Field
Author :
Wu, Ji-ying ; Ruan, Qiu-Qi
Author_Institution :
Inst. of Inf. Sci., Beijing Jiaotong Univ.
Volume :
2
fYear :
2006
fDate :
Aug. 30 2006-Sept. 1 2006
Firstpage :
338
Lastpage :
341
Abstract :
Partial differential equation (PDE) and Markov random field are two kinds of texture preserving regularized image denoising models. In this paper, the equivalence of them is proved: PDE can be derived to have the form of Markov model. Total variation (TV) is a kind of PDE, the adjacent domain of it is first order. Based on Markov theory, the adjacent domain of TV is enlarged to second order and it can contain more image information; image processed by the new TV-Markov model has little staircasing. In the new model, different coefficient function has different edge preserving property, so the new model is hybrid Using hybrid functions, the new TV-Markov model has better denoising effect, and it can preserve edge well
Keywords :
Markov processes; image denoising; image texture; partial differential equations; Markov random field; hybrid PDE denoising model; image texture; partial differential equation; total variation model; Biomedical imaging; Differential equations; Image denoising; Information science; Markov random fields; Noise reduction; Partial differential equations; Pixel; Radar imaging; TV;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Innovative Computing, Information and Control, 2006. ICICIC '06. First International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7695-2616-0
Type :
conf
DOI :
10.1109/ICICIC.2006.211
Filename :
1691995
Link To Document :
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