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A lossless image compression algorithm using predictive coding based on quantized colors

机译:基于量化色彩的基于预测编码的无损图像压缩算法

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Predictive coding has proven to be effective for lossless image compression. Predictive coding estimates a pixel color value based on the pixel color values of its neighboring pixels. To enhance the accuracy of the estimation, we propose a new and simple predictive coding that estimates the pixel color value based on the quantized pixel colors of three neighboring pixels. The prediction scheme can help minimize the upper bound of the residual errors from the prediction. Experiments were conducted on a set of true color 24-bit images, whose pixel colors were quantized into 2, 4, 8 and 16 colors. The experimental results show that the proposed algorithm outperforms some well known lossless image compression algorithms such as JPEG-LS and PNG by factors of 2-3 in terms of bits per pixel. The results also show that the proposed algorithm gives the best compression rates when colors were quantized into two colors.
机译:事实证明,预测编码对于无损图像压缩有效。预测编码基于其相邻像素的像素颜色值来估计像素颜色值。为了提高估计的准确性,我们提出了一种新的简单的预测编码,该编码基于三个相邻像素的量化像素颜色来估计像素颜色值。预测方案可以帮助最小化来自预测的残留误差的上限。对一组真彩色24位图像进行了实验,这些像素的像素颜色被量化为2、4、8和16种颜色。实验结果表明,所提出的算法在每像素位数方面比JPEG-LS和PNG等一些著名的无损图像压缩算法要好2-3倍。结果还表明,当将颜色量化为两种颜色时,该算法可提供最佳压缩率。

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