3-D Directional Diffusion

Author

Pop, Sorin ; Terebes, Romulus ; Borda, Monica ; Lavialle, Olivier ; Voicu, Lulian ; Baylou, Pierre

Author_Institution

Fac. of Electron. & Commun., Tech. Univ. of Cluj-Napoca

Volume

2

fYear

2005

fDate

21-24 Nov. 2005

Firstpage

955

Lastpage

958

Abstract

In this paper we propose a 3D filter for denoising and enhancing strongly oriented data. Our approach is based on 2D directional diffusion model proposed by Terebes et al. (2004). The diffusion process is modulated by a non-linear function depending on the absolute values of the directional derivatives in the 3 orthogonal directions of the space. These directions are the eigenvectors of a structure tensor. We compare this extension with an existing 3D extension designed by Dargent et al. (2004)

Keywords

eigenvalues and eigenfunctions; filtering theory; image denoising; image enhancement; tensors; 3D directional diffusion; 3D filtering; directional derivatives; eigenvectors; image denoising; image enhancement; nonlinear function; structure tensor; Acoustic reflection; Diffusion processes; Equations; Filtering; Geology; Noise reduction; Nonlinear filters; Seismic waves; Smoothing methods; Tensile stress; 3-D filtering; directional derivative; directional diffusion; structure tensor;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer as a Tool, 2005. EUROCON 2005.The International Conference on

Conference_Location

Belgrade

Print_ISBN

1-4244-0049-X

Type

conf

DOI

10.1109/EURCON.2005.1630105

Filename

1630105