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Received:May 31, 2010 Revised:July 06, 2010
Received:May 31, 2010 Revised:July 06, 2010
中文摘要: 分形维数是度量图像纹理粗糙度的一种常用方法，而依据分形维数的定义很难求解图像的分形维数。大量计算图像分形维数的算法被提出，但是这些方法往往基于不同的应用背景，没有总体比较和评价，多局限于差分盒子维的选用和改进，算法普遍存在计算误差较大，适应能力模糊的缺点。基于目前常用图像分形维数的计算方法，测试不同方法对图像粗糙度的敏感程度和时间复杂程度。从而对这些方法的适用范围进行分析和比较，给出应用的推荐模型。
Abstract:Fractal dimension is a commonly used method to measure texture coarseness. However, the definition of fractal dimension is very difficult to resolve. Many fractal dimension algorithms of image are proposed based on different application backgrounds. But they lack comparison and evaluation of the overall and are only limited to the selection of the box-counting dimension method. This paper makes a testing among these methods in sensitivity and time complexity for texture coarseness of image. Through a comparison and analysis to applicability of these methods, the recommended models are given at last.
keywords: fractal dimension(FD) box counting dimension (Counting box) sensitivity texture coarseness
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基金项目:国家自然科学基金:(60863010);973 前期计划专项课题(2010CB334709);新疆自然科学基金(2010211a19)
引用文本：
赵海英,杨光俊,徐正光.图像分形维数计算方法的比较.计算机系统应用,2011,20(3):238-241,246
ZHAO Hai-Ying,YANG Guang-Jun,XU Zheng-Guang.Comparison of Calculation Methods-Based Image Fractal Dimension.COMPUTER SYSTEMS APPLICATIONS,2011,20(3):238-241,246
赵海英,杨光俊,徐正光.图像分形维数计算方法的比较.计算机系统应用,2011,20(3):238-241,246
ZHAO Hai-Ying,YANG Guang-Jun,XU Zheng-Guang.Comparison of Calculation Methods-Based Image Fractal Dimension.COMPUTER SYSTEMS APPLICATIONS,2011,20(3):238-241,246
