DocumentCode :
3318797
Title :
Image Denoising Using Hybrid Model with Edge Preserving Capability
Author :
Chen, Bo ; Lai, Jianhuang ; Yuen, Pongchi
Author_Institution :
Sch. of Math. & Computational Sci., Sun Yat-Sen Univ., Guangzhou
Volume :
2
fYear :
2006
fDate :
3-6 Nov. 2006
Firstpage :
1779
Lastpage :
1784
Abstract :
The use of partial differential equations in image processing and computer vision has increased dramatically in recent years. The paper address to image denoising. A new model is introduced by extending alphabetaomega (ABO)-model in order to get high fidelity of the denoised images. To solve the model efficiently and reliably, we suggest a simple and symmetrical difference schemes and incorporate them with the essentially nondissipative difference (ENoD) schemes. We remove the impulse and Gaussian noises from different images and compare the PSNR values of the results with traditional filters. Numerical experimental results have shown the new model´s effectiveness in restoring images, especially in edge preservation and enhancement
Keywords :
Gaussian noise; computer vision; edge detection; image denoising; image enhancement; image restoration; impulse noise; partial differential equations; Gaussian noise; alphabetaomega model; computer vision; edge preservation; essentially nondissipative difference; image denoising; image enhancement; image processing; image restoration; impulse noise; partial differential equations; Additive noise; Computer vision; Gaussian noise; Image denoising; Image processing; Image restoration; Noise reduction; Nonlinear filters; PSNR; Sun;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Security, 2006 International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
1-4244-0605-6
Electronic_ISBN :
1-4244-0605-6
Type :
conf
DOI :
10.1109/ICCIAS.2006.295368
Filename :
4076274
Link To Document :
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