Improved method of nonlinear anistropic diffusion filtering based on open system

Weixin Wu; Hongchen Liu

doi:10.1117/12.750718

15 November 2007 Improved method of nonlinear anistropic diffusion filtering based on open system

Weixin Wu, Hongchen Liu

Proceedings Volume 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition; 678641 (2007) https://doi.org/10.1117/12.750718
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

Abstract

We propose an improved P-M nonlinear filter based anisotropic diffusion. In the new method, an open diffusion system is adopted to improve edge preservation in image denoising process. In the diffusion system, we choose part of pixels as "origin" pixels and "convergence" pixels. Value of these pixels does not change during filtering process. As a result, system energy exchange exists both within the system and between system and outer space. After filtering process, part of the noise energy is filtered out of the system. We test the performance of the new method and compare the result with Gaussian, P-M and Catte filter. Experimental results demonstrate the effectiveness in edge preservation of the new method.

Citation Download Citation

Weixin Wu and Hongchen Liu "Improved method of nonlinear anistropic diffusion filtering based on open system", Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 678641 (15 November 2007); https://doi.org/10.1117/12.750718

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available