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Segmented Optimal Linear Prediction applied to Lossless Image Coding

机译:分段的最佳线性预测应用于无损图像编码

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Most lossless coding techniques use prediction to reduce first order entropy of pixels followed by a data compression scheme like Huffman Coding, Lempel Ziv algorithm or Arithmetic Coding. In this work it is presented a prediction scheme that uses linear coefficients optimized by regions of the set where prediction base pixels lie. This technique was applied to several test images. First order entropies and conditional first order entropies were measured and compared with figures obtained using the well known Median Adaptive Predictor (M.A.P.). It is observed that M.A.P. is a particular case of our scheme with non-optimized coefficients.
机译:大多数无损编码技术使用预测来减少像素的第一订单熵,然后是霍夫曼编码,LEMPEL ZIV算法或算术编码等数据压缩方案。在这项工作中,呈现了一种预测方案,该预测方案使用由预测基本像素所呈现的集合的区域优化的线性系数。该技术应用于几个测试图像。测量第一订单熵和条件第一订单熵,并与使用众所周知的中值自适应预测器(M.A.P.)获得的图进行比较。观察到m.a.p.是我们具有非优化系数的特定情况。

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