The two-dimensional adaptive LMS (TDLMS) algorithm

Author

Hadhoud, Mohiy M. ; Thomas, David W.

Author_Institution

Dept. of Electron. & Inf. Process., Southampton Univ., UK

Volume

35

Issue

5

fYear

1988

fDate

5/1/1988 12:00:00 AM

Firstpage

485

Lastpage

494

Abstract

A two-dimensional least-mean-square (TDLMS) adaptive algorithm based on the method of steepest decent is proposed and applied to noise reduction in images. The adaptive property of the TDLMS algorithm enables the filter to have an improved tracking performance in nonstationary images. The results presented show that the TDLMS algorithm can be used successfully to reduce noise in images. The algorithm complexity is 2(N×N) multiplications and the same number of additions per image sample, where N is the parameter-matrix dimension. Analysis and convergence properties of the LMS algorithm in the one-dimensional case presented by other authors is shown to be applicable to this algorithm. The algorithm can be used in a number of two-dimensional applications such as image enhancement and image data processing

Keywords

adaptive systems; computerised picture processing; least squares approximations; TDLMS algorithm; adaptive algorithm; algorithm complexity; convergence properties; image data processing; image enhancement; method of steepest decent; noise reduction in images; nonstationary images; parameter-matrix dimension; tracking performance; two-dimensional adaptive LMS; Adaptive algorithm; Adaptive filters; Equations; Filtering; Image enhancement; Image processing; Least squares approximation; Signal processing algorithms; Statistics; Wiener filter;

fLanguage

English

Journal_Title

Circuits and Systems, IEEE Transactions on

Publisher

ieee

ISSN

0098-4094

Type

jour

DOI

10.1109/31.1775

Filename

1775