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A fast classification based method for fractal image encoding

机译:基于快速分类的分形图像编码方法

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In the present paper a fast and efficient fractal image encoding method based on classification of image blocks is presented. Two parameters are used to sort image blocks into disjoint classes: the direction of the approximate first derivative and a normalized root mean square error of the fitting plane in the given block. With the help of these parameters the number of domain blocks examined for a range block is reduced dramatically, and thus, the classification results in a considerable acceleration of the encoding process, without loss of the reconstruction fidelity. The proposed method is compared to recently developed fast classification algorithms and a 'No search algorithm', and its rate-distortion performance under the same encoding time limit is proved to be better than that of the others.
机译:本文提出了一种基于图像块分类的快速有效的分形图像编码方法。两个参数用于将图像块分类为不相交的类别:给定块中近似一阶导数的方向和拟合平面的归一化均方根误差。借助于这些参数,针对范围块检查的域块的数量显着减少,因此,分类可显着加速编码过程,而不会损失重建保真度。将该方法与最新开发的快速分类算法和“无搜索算法”进行了比较,证明了在相同编码时限下的码率失真性能优于其他方法。

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