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    王相海, 张文雅, 邢俊宇, 吕芳, 穆振华. 高阶次Caputo型分数阶微分算子及其图像增强应用[J]. 计算机研究与发展, 2023, 60(2): 448-464. DOI: 10.7544/issn1000-1239.202110942
    引用本文: 王相海, 张文雅, 邢俊宇, 吕芳, 穆振华. 高阶次Caputo型分数阶微分算子及其图像增强应用[J]. 计算机研究与发展, 2023, 60(2): 448-464. DOI: 10.7544/issn1000-1239.202110942
    Wang Xianghai, Zhang Wenya, Xing Junyu, Lü Fang, Mu Zhenhua. High-order Caputo Fractional Order Differential Operator and Its Application in Image Enhancement[J]. Journal of Computer Research and Development, 2023, 60(2): 448-464. DOI: 10.7544/issn1000-1239.202110942
    Citation: Wang Xianghai, Zhang Wenya, Xing Junyu, Lü Fang, Mu Zhenhua. High-order Caputo Fractional Order Differential Operator and Its Application in Image Enhancement[J]. Journal of Computer Research and Development, 2023, 60(2): 448-464. DOI: 10.7544/issn1000-1239.202110942

    高阶次Caputo型分数阶微分算子及其图像增强应用

    High-order Caputo Fractional Order Differential Operator and Its Application in Image Enhancement

    • 摘要: 近年来基于分数阶微积分的信号和图像处理受到广泛关注. 目前常见的应用于图像处理的分数阶微分算子包括G-L(Grünwald-Letnikov)型、R-L(Riemann-Liouville)型和Caputo型3种.G-L和R-L算子尽管能对图像有着一定的增强效果,但其对图像对比度、清晰度的提升有限;而Caputo型微分掩模算子目前多限于(0,1)阶的低阶算子,其高阶次算子的研究和应用相对较少.对高阶次Caputo型分数阶微分算子及其图像增强应用进行研究,首先针对(1,2)阶、(2,3)阶次Caputo型分数阶微分构建一种基于向前差分的微分掩模算子,并对其误差进行了论证;其次进一步给出了更高阶次Caputo型分数阶微分算子的矩阵化表现形式;最后在此基础上将所提出的高阶次Caputo型分数阶微分掩模算子应用于图像增强.实验结果表明所提出的高阶次Caputo型分数阶微分算子取得了很好的图像增强效果,对提升图像的对比度、清晰度和平均梯度具有较为明显的优势.

       

      Abstract: Unlike the traditional integer calculus, which usually has intuitive geometric and physical meaning, the definition of fractional calculus is generally complex and presents different forms. However, its characteristics such as memory and nonlocality have laid a good mathematical foundation for solving some complex problems in the engineering field. At the same time, signal and image processing based on fractional calculus have also attracted attention in recent years. At present, the common fractional differential operators used in image processing include Grünwald-Letnikov (G-L) fractional differential, Riemann-Liouville (R-L) fractional differential and Caputo fractional differential. Although G-L and R-L operators can enhance the image to a certain extent, their capabilites of the improvement of image contrast and definition is limited. At present, Caputo differential mask operators are mostly limited to low-order operators of order in (0,1), and the research and application of high-order operators are relatively few. In this paper, the high-order Caputo fractional differential operator and its application in image enhancement are studied. Firstly, a differential mask operator based on forward difference is constructed for Caputo fractional differential with order in (1,2) and (2,3), and its error is demonstrated; Further, the general form of high-order Caputo fractional differential operator is studied, and a representation based on matrix is given. On this basis, the proposed high-order Caputo fractional differential mask operator is applied to image enhancement, and the comparative experiments of image enhancement are carried out for mask operators of different orders and sizes. The experimental results show that the proposed high-order Caputo fractional differential operator achieves good image enhancement effect, especially for improving image contrast, clarity and average gradient have obvious advantages.

       

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