Edge-preserving image denoising and estimation of discontinuous surfaces

Author

Gijbels, I. ; Lambert, A. ; Qiu, P.

Author_Institution

Dept. of Math., Leuven Univ., Heverlee

Volume

28

Issue

7

fYear

2006

fDate

7/1/2006 12:00:00 AM

Firstpage

1075

Lastpage

1087

Abstract

In this paper, we are interested in the problem of estimating a discontinuous surface from noisy data. A novel procedure for this problem is proposed based on local linear kernel smoothing, in which local neighborhoods are adapted to the local smoothness of the surface measured by the observed data. The procedure can therefore remove noise correctly in continuity regions of the surface and preserve discontinuities at the same time. Since an image can be regarded as a surface of the image intensity function and such a surface has discontinuities at the outlines of objects, this procedure can be applied directly to image denoising. Numerical studies show that it works well in applications, compared to some existing procedures

Keywords

edge detection; image denoising; regression analysis; discontinuous surface estimation; edge-preserving image denoising; image intensity function; linear kernel smoothing; noisy data; statistical jump regression analysis; Adaptive filters; Application software; Bayesian methods; Filtering; Image denoising; Image restoration; Kernel; Smoothing methods; Surface cleaning; Surface fitting; Corners; edges; jump-preserving estimation; local linear fit; noise; nonparametric regression; smoothing; surface fitting; weighted residual mean square.; Algorithms; Artifacts; Artificial Intelligence; Computer Simulation; Image Enhancement; Image Interpretation, Computer-Assisted; Information Storage and Retrieval; Models, Statistical; Pattern Recognition, Automated;

fLanguage

English

Journal_Title

Pattern Analysis and Machine Intelligence, IEEE Transactions on

Publisher

ieee

ISSN

0162-8828

Type

jour

DOI

10.1109/TPAMI.2006.140

Filename

1634339