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New ADPCM image coder using frequency weighted directional filters

机译:使用频率加权定向滤波器的新型ADPCM图像编码器

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Abstract: This paper proposes a new ADPCM method for image coding called directional ADPCM which can remove more redundancy from the image signals than the conventional ADPCM. The conventional ADPCM calculates the two-dimensional prediction coefficients by using the correlation functions followed by solving the Yule-Walker equation. Actually, the quantities of correlation functions to be the approximation of the correlation function. However, the block size is limited by the error accumulation effect during packet transmission. Using small block may induce the unregulated prediction coefficients. Therefore, we need to develop the directional ADPCM system to overcome such a problem and to have better prediction result. Our directional ADPCM utilized the fan- shape filters to obtain the energy distribution in four directions and then determines the four directional prediction coefficient. All the fan-shape filters are designed by using the singular value decomposition (SVD) method, the two-dimensional Hilbert transform technique, and the frequency weighting concept. In the experiments, we illustrate that the M.S.E. for the directional ADPCM is less than that of the conventional ADPCM.!10
机译:摘要:本文提出了一种新的用于图像编码的ADPCM方法,称为定向ADPCM,与传统的ADPCM相比,该方法可以从图像信号中消除更多的冗余。常规的ADPCM通过使用相关函数接着求解Yule-Walker方程来计算二维预测系数。实际上,相关函数的数量是相关函数的近似值。然而,块大小受到分组传输期间的错误累积效应的限制。使用小块可能会导致未调整的预测系数。因此,我们需要开发定向ADPCM系统以克服该问题并具有更好的预测结果。我们的定向ADPCM利用扇形滤波器获得四个方向的能量分布,然后确定四个方向的预测系数。所有扇形滤波器均采用奇异值分解(SVD)方法,二维Hilbert变换技术和频率加权概念进行设计。在实验中,我们说明了M.S.E.定向ADPCM的角度小于传统ADPCM。!10

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