Adaptive filters based on local estimates

Author

Sun, X.Z. ; Venetsanopoulos, A.N.

Author_Institution

Dept. of Electr. Eng., Changsha Railway Inst., Hunan, China

fYear

1988

fDate

7-9 June 1988

Firstpage

2549

Abstract

Adaptive schemes for noise filtering and edge detection of digital signals are developed which are based on the minimum mean square error (MMSE) estimate of the information bearing signal corrupted by additive noise. The MMSE estimate is computed using the local statistics of the input signal and noise. The output is fed back to the input and the difference between the input and the output is used as the noise estimator. The local statistics of signal and noise are computed through a moving signal window and a moving noise window, which are over the input signal and the noise estimator, respectively. These schemes change their performance according to the local SNR (signal-to-noise ratio) adaptively and have almost optimal filtering performance at homogeneous (low-SNR) regions of the signal and preserve edge information at edge (high-SNR) regions as well as the median filter. Two kinds of adaptive filtering algorithms and an edge-detection algorithm are considered.<>

Keywords

adaptive filters; digital filters; filtering and prediction theory; interference suppression; picture processing; random noise; MMSE estimate; SNR; adaptive filtering algorithms; additive noise; digital filters; digital signals; edge detection; image processing; local estimates; local statistics; minimum mean square error; moving noise window; moving signal window; noise estimator; noise filtering; Adaptive filters; Additive noise; Digital filters; Filtering algorithms; Image edge detection; Information filtering; Information filters; Signal detection; Signal to noise ratio; Statistics;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 1988., IEEE International Symposium on

Conference_Location

Espoo, Finland

Type

conf

DOI

10.1109/ISCAS.1988.15461

Filename

15461