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