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An Improved Differential Box-Counting Approach to Compute Fractal Dimension of Gray-Level Image

机译:一种改进的差分盒计数方法来计算灰度级图像的分形维数

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摘要

The box counting dimension is widely used for the image processing task. In this paper, The key problems involved in the computation of differential box counting are discussed, which are the range of linear scales and the precise number of boxes, etc, then the precise computing method for box counting dimension is presented. Experiments have been performed on three kinds of images, i.e., synthetic noise images, natural textured images and infrared smoke screen jamming images. The results show that, compared with the traditional differential box counting dimension, the proposed approach not only has more precise estimated value of fractal dimension, but also consumes less computational time.
机译:盒子计数尺寸广泛用于图像处理任务。在本文中,讨论了算子计数计算的关键问题,这是线性比例的范围和精确的盒子等,然后呈现了框计数维度的精确计算方法。已经在三种图像上进行了实验,即合成噪声图像,自然纹理图像和红外烟幕干扰图像。结果表明,与传统的差分框计数尺寸相比,所提出的方法不仅具有更精确的分形维数值,而且还消耗了较少的计算时间。

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