DocumentCode :
2605964
Title :
A fourth-order partial differential equations method of noise removal
Author :
Liu, Xilin ; Ying, Zhengwei ; Qiu, Shufang
Author_Institution :
Dept. of Math., East China Inst. of Technol., Nanchang, China
Volume :
2
fYear :
2011
fDate :
15-17 Oct. 2011
Firstpage :
641
Lastpage :
645
Abstract :
In this paper, we introduce a new method for image denoising based on a fourth-order partial differential equation (PDE) model and a mean curvature diffusion (MCD) model. The fourth-order PDE model can cause less blocky effect and preserve edges in image denoising. But it loses too much texture in the restored image. The mean curvature diffusion model can keep texture while quickly removing noise. So we introduce the mean curvature diffusion into the PDE-based noise removal algorithm. Finally, Numerical experiments are done by our proposed model. We also compared our method with the fourth-order PDE model and the mean curvature diffusion model. Numerical examples show that the proposed model can preserve fine structure and keep texture well while quickly removing image´s noise.
Keywords :
image denoising; image enhancement; image restoration; image texture; partial differential equations; fourth-order PDE model; fourth-order partial differential equation method; image denoising; image restoration; image texture; mean curvature diffusion model; noise removal method; Gaussian noise; Mathematical model; Noise measurement; Noise reduction; Numerical models; PSNR;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image and Signal Processing (CISP), 2011 4th International Congress on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-9304-3
Type :
conf
DOI :
10.1109/CISP.2011.6100378
Filename :
6100378
Link To Document :
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