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

  • Authors:
  • Y. -S. Chung;M. Kanefsky

  • Affiliations:
  • Dept. of Electr. Eng., Pittsburgh Univ., PA;-

  • Venue:
  • IEEE Transactions on Image Processing
  • Year:
  • 1992

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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