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

机译:关于使用ARMA预测对图像进行ADPCM编码的二维递归LMS算法

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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.
机译:具有自回归移动平均值(ARMA)表示以及偏置项的二维(2D)线性预测器适用于非负图像的自适应差分脉冲编码调制(ADPCM)编码。通过使用2D递归LMS(TRLMS)算法来更新预测系数。提出了收敛因子最优值的约束条件和基于约束条件的更新算法。可以使用稳定性控制因子来修改系数更新算法。该实现可以在空间域中实时地进行。对真实图像进行了三种不同类型的预测变量的比较。与AR算法相比,ARMA预测器显示出更高的性能。

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