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A new approach for the speed up of fractal image coding

机译:一种加快分形图像编码速度的新方法

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摘要

We propose a time improved fractal image coder with a reduceddomain pool and optimal luminance transform parameters calculation. Thisscheme is applicable to the Fischer's (1994) classification method. Weaccelerate the encoding process by reducing the domain pool and then byminimizing the number of operations for the similarity search; thisreduction is based on discarding the domains with nearly the samevariance from each class of the domain pool. This approach provides agreater speed loss with a slight loss in the compression ratio and aslight improvement in the image quality. In our experiments anacceleration of 6.7 for the image “Lena” is reached with agood decoded image quality. For a speed up factor of 2 the compressionratio is about 0.8% reduced and the image quality is about 0.23%improved. In order to increase the compression ratio again we useJaquin's (1992) method and we remove some of the range blocks with shadeproperty from the search
机译:我们提出了一种时间改进的分形图像编码器,具有减少的 域池和最佳亮度变换参数计算。这 该方案适用于Fischer(1994)的分类方法。我们 通过减少域池,然后通过减少编码来加速编码过程 减少相似搜索的操作次数;这 减少是基于丢弃几乎相同的域 与域池的每个类的差异。这种方法提供了 更大的速度损失,压缩比略有损失,并且 图像质量略有改善。在我们的实验中 图像“ Lena”的加速度为6.7, 良好的解码图像质量。对于2的加速因子,压缩 比例降低约0.8%,图像质量降低约0.23% 改善。为了再次提高压缩率,我们使用 Jaquin(1992)的方法,我们删除了一些带有阴影的范围块 搜索中的属性

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