On 2-D recursive LMS algorithms using ARMA prediction for ADPCM encoding of images

Author

Chung, Young-Sik ; Kanefsky, Morton

Author_Institution

Dept. of Electr. Eng., Pittsburgh Univ., PA, USA

Volume

1

Issue

3

fYear

1992

fDate

7/1/1992 12:00:00 AM

Firstpage

416

Lastpage

422

Abstract

A two-dimensional (2D) linear predictor which has an autoregressive moving average (ARMA) representation well as a bias term is adapted for adaptive differential pulse code modulation (ADPCM) encoding of nonnegative images. The predictor coefficients are updated by using a 2D recursive LMS (TRLMS) algorithm. A constraint on optimum values for the convergence factors and an updating algorithm based on the constraint are developed. The coefficient updating algorithm can be modified with a stability control factor. This realization can operate in real time and in the spatial domain. A comparison of three different types of predictors is made for real images. ARMA predictors show improved performance relative to an AR algorithm

Keywords

encoding; filtering and prediction theory; least squares approximations; picture processing; pulse-code modulation; 2D linear predictor; ADPCM encoding; ARMA prediction; adaptive differential pulse code modulation; autoregressive moving average; bias term; convergence factors; image encoding; nonnegative images; real time; recursive LMS algorithms; spatial domain; stability control factor; updating algorithm; Convergence; Image coding; Image reconstruction; Least squares approximation; Modulation coding; Poles and zeros; Prediction algorithms; Pulse modulation; Quantization; Two dimensional displays;

fLanguage

English

Journal_Title

Image Processing, IEEE Transactions on

Publisher

ieee

ISSN

1057-7149

Type

jour

DOI

10.1109/83.148614

Filename

148614