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A square non-symmetry and anti-packing model representation algorithm of gray images using binary bit-plane decomposition

机译:基于二进制位平面分解的灰度图像平方非对称和反打包模型表示算法

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Complexity of gray images can be effectively reduced when the binary bit-plane decomposition (BPD) approach is used. Taking a square subpattern record into consideration, it needs to make a record of a side and a starting point. However, taking into account a triangle subpattern record, it needs to make a record of the three vertices of a triangle. Therefore, a square subpattern is able to effectively cut back the storage room when we compare these two kinds of subpatterns, which is a significant strong point of the square subpattern. In this paper, motivated by this strong point, by studying the nonoverlapping square subpattern, we put forward a square non-symmetry and antipacking model (SNAM) representation algorithm of gray images based on the BPD approach, which is named as the SNAMBPD algorithm. The experimental results in our paper verify that our proposed algorithm is better than the triangle NAM (TNAM) representation algorithm of gray images based on the BPD approach with regard to the number of the subpatterns and the storage room.
机译:当使用二进制比特平面分解(BPD)方法时,可以有效地减少灰度图像的复杂性。考虑正方形子模式记录,需要创造一面的记录和起点。但是,考虑到三角形子图案记录,需要制作三角形的三个顶点的记录。因此,当我们比较这两种子模式时,可以有效地将储藏室有效地剪切储藏室,这是方形图案的重要强点。在本文中,通过这种强点的激励,通过研究非传播的方形图案,我们提出了基于BPD方法的灰色图像的正方形非对称性和防擒出模型(Snam)表示算法,其被命名为Snambpd算法。我们的论文中的实验结果验证了我们所提出的算法优于基于BPD方法的三角形NAM(TNAM)表示算法,关于子模式和存储室的数量。

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