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Multifractal Framework Based on Blanket Method

机译:基于一揽子方法的多重分形框架

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摘要

This paper proposes two local multifractal measures motivated by blanket method for calculation of fractal dimension. They cover both fractal approaches familiar in image processing. The first two measures (proposed Methods 1 and 3) support model of image with embedded dimension three, while the other supports model of image embedded in space of dimension three (proposed Method 2). While the classical blanket method provides only one value for an image (fractal dimension) multifractal spectrum obtained by any of the proposed measures gives a whole range of dimensional values. This means that proposed multifractal blanket model generalizes classical (monofractal) blanket method and other versions of this monofractal approach implemented locally. Proposed measures are validated on Brodatz image database through texture classification. All proposed methods give similar classification results, while average computation time of Method 3 is substantially longer.
机译:本文提出了两种基于盖层法的局部多重分形测量方法,以计算分形维数。它们涵盖了图像处理中熟悉的两种分形方法。前两个措施(建议的方法1和3)支持具有嵌入维3的图像模型,而其他措施则支持在维度3的空间中嵌入图像的模型(建议方法2)。虽然经典的橡皮布方法仅为图像(分形维数)提供一个值,但通过任何建议的措施获得的多重分形光谱都提供了整个维数范围。这意味着,建议的多重分形覆盖模型可以概括经典的(单形)覆盖方法以及在本地实施的该单形方法的其他版本。通过纹理分类在Brodatz图像数据库上验证了建议的措施。所有提出的方法都给出相似的分类结果,而方法3的平均计算时间则明显更长。

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