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An edge property-based neighborhood region search strategy for fractal image compression

机译:分形图像压缩的基于边缘属性的邻域搜索策略

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In this paper, an edge property-based neighborhood region search method is proposed to speedup the fractal encoder. The method searches for the best matched solution in the frequency domain. A coordinate system is constructed using the two lowest discrete cosine transformation (DCT) coefficients of image blocks. Image blocks with similar edge shapes will be concentrated in some specific regions. Therefore the purpose of speedup can be reached by limiting the search space. Moreover, embedding the edge property of block into the proposed search method, the speedup rate can be lifted further. Experimental results show that, under the condition of the same PSNR, the encoding time of the proposed method is only about two-fifth of Dun's classification method. Compared with Tseng's method, the proposed method is near or superior to the performance of their method. Moreover, the encoding speed of the proposed method is about 120 times faster than that of the full search method, while the penalty of retrieved image quality is only decaying 0.9 dB.
机译:本文提出了一种基于边缘属性的邻域搜索方法,以加快分形编码器的速度。该方法在频域中搜索最佳匹配的解决方案。使用图像块的两个最低离散余弦变换(DCT)系数构造坐标系。具有相似边缘形状的图像块将集中在某些特定区域。因此,可以通过限制搜索空间来达到加速的目的。此外,将块的边缘属性嵌入到提出的搜索方法中,可以进一步提高加速率。实验结果表明,在相同的PSNR条件下,该方法的编码时间仅为Dun's分类法的五分之二。与Tseng的方法相比,该方法的性能接近或优于其方法。而且,所提出的方法的编码速度比完全搜索方法的编码速度快约120倍,而检索到的图像质量的损失仅衰减了0.9dB。

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