Nonlinear multiscale filtering

Author

Pollak, Ilya

Volume

19

Issue

5

fYear

2002

fDate

9/1/2002 12:00:00 AM

Firstpage

26

Lastpage

36

Abstract

In this article, we give an overview of scale-spaces and their application to noise suppression and segmentation of 1-D signals and 2-D images. Several prototypical problems serve as our motivation. We review several scale-spaces (linear Gaussian, Perona-Malik, and SIDE-stabilized inverse diffusion equation) and discuss their advantages and shortcomings. We describe our previous work and argue that a very simple nonlinear scale-space leads to a fast estimation algorithm which produces accurate segmentations and estimates of signals and images.

Keywords

image enhancement; image processing; image restoration; image segmentation; interference suppression; noise; nonlinear filters; 1-D signals; 2-D images; Perona-Malik scale space; SIDE scale space; fast estimation algorithm; linear Gaussian scale space; noise suppression; nonlinear multiscale filtering; nonlinear scale-space; segmentation; segmentations; stabilized inverse diffusion equation; Discrete wavelet transforms; Filtering; Filters; Image analysis; Image restoration; Image segmentation; Maximum likelihood estimation; Signal analysis; Signal processing algorithms; Signal restoration;

fLanguage

English

Journal_Title

Signal Processing Magazine, IEEE

Publisher

ieee

ISSN

1053-5888

Type

jour

DOI

10.1109/MSP.2002.1028350

Filename

1028350