Morphological anisotropic diffusion

Author

Segall, C. Andrew ; Acton, Scott T.

Author_Institution

Sch. of Electr. & Comput. Eng., Oklahoma State Univ., Stillwater, OK, USA

Volume

3

fYear

1997

Firstpage

348

Abstract

Current formulations of anisotropic diffusion are unable to prevent feature drift and smooth small regions. These deficiencies reduce the effectiveness of the diffusion operation in many image processing tasks, including segmentation, edge detection, compression, and multiscale processing. This paper introduces a morphological diffusion coefficient capable of smoothing small objects while maintaining edge locality. Results are presented that demonstrate its efficacy in edge detection tasks

Keywords

edge detection; image representation; image segmentation; iterative methods; mathematical morphology; smoothing methods; approximation; edge detection; edge locality; feature drift; image compression; image processing; image representation; image segmentation; iterative solution; morphological anisotropic diffusion; morphological diffusion coefficient; multiscale processing; smooth small regions; Adaptive filters; Anisotropic magnetoresistance; Equations; Filtering; Image edge detection; Image processing; Kernel; Laboratories; Nonlinear filters; Smoothing methods;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 1997. Proceedings., International Conference on

Conference_Location

Santa Barbara, CA

Print_ISBN

0-8186-8183-7

Type

conf

DOI

10.1109/ICIP.1997.632112

Filename

632112