Partial differential equations have recently become popular and useful tools for several image processing tasks such as image denoising and segmentation. In this work we implement a unified image denoising and segmentation approach which is based on a nonlinear diffusion equation with a reactive term for achieving edge preserving smoothing and segmentation. This model is highly nonlinear and the computation of the gaussian low pass filter at the intermediate time steps is computationally very time consuming. In order to speed up the process a coupled system is efficiently implemented using Comsol Multiphysics. The filter obtained has variance parameter changing in the integration interval. Comsol Multiphysics results a valuable tool for projecting and testing filtering techniques both in the teaching as well as research activity.

Image Denoising and Segmentation using COMSOL Multiphysics

ZAMA, FABIANA
2007

Abstract

Partial differential equations have recently become popular and useful tools for several image processing tasks such as image denoising and segmentation. In this work we implement a unified image denoising and segmentation approach which is based on a nonlinear diffusion equation with a reactive term for achieving edge preserving smoothing and segmentation. This model is highly nonlinear and the computation of the gaussian low pass filter at the intermediate time steps is computationally very time consuming. In order to speed up the process a coupled system is efficiently implemented using Comsol Multiphysics. The filter obtained has variance parameter changing in the integration interval. Comsol Multiphysics results a valuable tool for projecting and testing filtering techniques both in the teaching as well as research activity.
2007
Proceedings of the European Comsol Conference 2007
494
497
F. Zama
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/51975
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