Saddle-node dynamics for edge-preserving and scale-space filtering

Author

Wong, Yiu-fai

Author_Institution

Div. of Eng., Texas Univ., San Antonio, TX, USA

Volume

1

fYear

1994

fDate

13-16 Nov 1994

Firstpage

840

Abstract

Demonstrates the use of saddle-node dynamics for edge-preserving and scale-space filtering. The filter is derived from the maximum entropy principle and an analogy with statistical physics. The filter is governed by a single scale parameter which dictates the spatial extent of nearby data used for determining the output. This filter is thus highly adaptive and data-driven. It provides a mechanism for a) removing impulsive noise; b) improved smoothing of nonimpulsive noise and c) preserving edges. Comparisons with conventional techniques are made using real images

Keywords

adaptive filters; digital filters; edge detection; interference suppression; maximum entropy methods; smoothing methods; adaptive data-driven filter; edge-preserving filtering; images; impulsive noise; maximum entropy principle; nearby data; nonimpulsive noise; output; saddle-node dynamics; scale-space filtering; single scale parameter; smoothing; spatial extent; statistical physics; Adaptive filters; Anisotropic magnetoresistance; Computer vision; Costs; Entropy; Filtering; Physics; Pixel; Robustness; Smoothing methods;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 1994. Proceedings. ICIP-94., IEEE International Conference

Conference_Location

Austin, TX

Print_ISBN

0-8186-6952-7

Type

conf

DOI

10.1109/ICIP.1994.413433

Filename

413433