Image enhancement segmentation and denoising by time dependent nonlinear diffusion processes

G. Gilboa; Y. Y. Zeevi; N. Sochen

Image enhancement segmentation and denoising by time dependent nonlinear diffusion processes

G. Gilboa^*, Y. Y. Zeevi, N. Sochen

^*Corresponding author for this work

Technion-Israel Institute of Technology

Research output: Contribution to conference › Paper › peer-review

22 Scopus citations

Abstract

Two nonlinear diffusion processes with time-dependent diffusion coefficients are presented. Both processes converge to nontrivial solutions, eliminating the need to impose an arbitrary diffusion stopping time, otherwise required in the implementation of most nonlinear diffusion processes. The two schemes employ nonlinear cooling mechanisms that preserve edges. One scheme is intended for general denoising, whereas the other is targeted for enhancement or segmentation of images. Simulation results indicate that the proposed schemes provide a stable and efficient tool for processing of noisy images.

Original language	English
Pages	134-137
Number of pages	4
State	Published - 2001
Externally published	Yes
Event	IEEE International Conference on Image Processing (ICIP) - Thessaloniki, Greece Duration: 7 Oct 2001 → 10 Oct 2001

Conference

Conference	IEEE International Conference on Image Processing (ICIP)
Country/Territory	Greece
City	Thessaloniki
Period	7/10/01 → 10/10/01

Keywords

Anisotropic diffusion
Image denoising
Image enhancement
Nonlinear diffusion
Time-dependent diffusion

Cite this

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title = "Image enhancement segmentation and denoising by time dependent nonlinear diffusion processes",

abstract = "Two nonlinear diffusion processes with time-dependent diffusion coefficients are presented. Both processes converge to nontrivial solutions, eliminating the need to impose an arbitrary diffusion stopping time, otherwise required in the implementation of most nonlinear diffusion processes. The two schemes employ nonlinear cooling mechanisms that preserve edges. One scheme is intended for general denoising, whereas the other is targeted for enhancement or segmentation of images. Simulation results indicate that the proposed schemes provide a stable and efficient tool for processing of noisy images.",

keywords = "Anisotropic diffusion, Image denoising, Image enhancement, Nonlinear diffusion, Time-dependent diffusion",

author = "G. Gilboa and Zeevi, {Y. Y.} and N. Sochen",

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AU - Gilboa, G.

AU - Zeevi, Y. Y.

AU - Sochen, N.

PY - 2001

Y1 - 2001

N2 - Two nonlinear diffusion processes with time-dependent diffusion coefficients are presented. Both processes converge to nontrivial solutions, eliminating the need to impose an arbitrary diffusion stopping time, otherwise required in the implementation of most nonlinear diffusion processes. The two schemes employ nonlinear cooling mechanisms that preserve edges. One scheme is intended for general denoising, whereas the other is targeted for enhancement or segmentation of images. Simulation results indicate that the proposed schemes provide a stable and efficient tool for processing of noisy images.

AB - Two nonlinear diffusion processes with time-dependent diffusion coefficients are presented. Both processes converge to nontrivial solutions, eliminating the need to impose an arbitrary diffusion stopping time, otherwise required in the implementation of most nonlinear diffusion processes. The two schemes employ nonlinear cooling mechanisms that preserve edges. One scheme is intended for general denoising, whereas the other is targeted for enhancement or segmentation of images. Simulation results indicate that the proposed schemes provide a stable and efficient tool for processing of noisy images.

KW - Anisotropic diffusion

KW - Image denoising

KW - Image enhancement

KW - Nonlinear diffusion

KW - Time-dependent diffusion

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T2 - IEEE International Conference on Image Processing (ICIP)

Y2 - 7 October 2001 through 10 October 2001

ER -

Image enhancement segmentation and denoising by time dependent nonlinear diffusion processes

Abstract

Conference

Keywords

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