Robust local max-min filters by normalized power-weighted filtering

Author

van Vliet, L.J.

Author_Institution

Dept. of Imaging Sci. & Technol., Delft Univ. of Technol., Netherlands

Volume

1

fYear

2004

fDate

23-26 Aug. 2004

Firstpage

696

Abstract

A normalized, power-weighted averaging filter (NPF) is a very good approximation to the well-known local maximum and minimum filters along the object edges and offers noise reduction in the foreground and background regions. This favorable combination turns out to be very effective in image smoothing, edges detection and image sharpening. It offers a clear improvement over the existing operators based on true max-min filtering. Our filter can be implemented very efficiently by a table lookup (for the power) and two (separable) convolutions.

Keywords

approximation theory; edge detection; image denoising; minimax techniques; smoothing methods; approximation theory; convolution method; edges detection; image sharpening; image smoothing; noise reduction; normalized power weighted filtering; robust local maximum filters; robust local minimum filters; Filtering; Filters; Image edge detection; Image processing; Kernel; Noise reduction; Robustness; Smoothing methods; Table lookup; Uniform resource locators;

fLanguage

English

Publisher

ieee

Conference_Titel

Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on

ISSN

1051-4651

Print_ISBN

0-7695-2128-2

Type

conf

DOI

10.1109/ICPR.2004.1334273

Filename

1334273