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Fractional differential approach to detecting textural features of digital image and its fractional differential filter implementation

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Science in China(Series F) 2008年第9期51卷 1319-1339页

作者： pu yifei WANG WeiXing ZHOU JiLiu WANG YiYang JIA HuaDing School of Computer Science and Technology Sichuan University Chengdu 610064 China School of Electronic Engineering University of Electronic Science and Technology of China Chengdu610054 China Academie des Sciences de I'lnstitue de France 28 rue Saint-Dominique 75007 Paris France Laboratoire de I'IADI ERI (INSERM-UHP) au CHU de Nancy Brabois Universite Henri Poincare(Nancy I)54511 Vandoeuvre les Nancy France School of Electronics and Information Sichuan University Chengdu 610064 China

This paper mainly discusses fractional differential approach to detecting textural features of digital image and its fractional differential filter. Firstly, both the geo- metric meaning and the kinetic physical meaning of fractional differential are clearly explained in view of information theory and kinetics, respectively. Secondly, it puts forward and discusses the definitions and theories of fractional stationary point, fractional equilibrium coefficient, fractional stable coefficient, and fractional grayscale co-occurrence matrix. At the same time, it particularly discusses frac- tional grayscale co-occurrence matrix approach to detecting textural features of digital image. Thirdly, it discusses in detail the structures and parameters of nxn any order fractional differential mask on negative x-coordinate, positive x-coordi- nate, negative y-coordinate, positive y-coordinate, left downward diagonal, left upward diagonal, right downward diagonal, and right upward diagonal, respectively. Furthermore, it discusses the numerical implementation algorithms of fractional differential mask for digital image. Lastly, based on the above-mentioned discus- sion, it puts forward and discusses the theory and implementation of fractional differential filter for digital image. Experiments show that the fractional differential-based image operator has excellent feedback for enhancing the textural details of rich-grained digital images.

关键词： fractional stationary point fractional equilibrium coefficient fractional stable coefficient fractional grayscale co-occurrence matrix fractional differential mask

Fractional partial differential equation denoising models for texture image

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Science China(Information Sciences) 2014年第7期57卷 184-202页

作者： pu yifei SIARRY Patrick ZHOU JiLiu LIU YiGuang ZHANG Ni HUANG Guo LIU YiZhi School of Computer Science and Technology Sichuan University Universit de Paris 12 (LiSSi E.A.3956) 61 av.du Gnral de Gaulle94010 CRETEIL CedexFrance Library of Sichuan University Sichuan University Computer Science College Leshan Normal University Wu Yuzhang Honors College of Sichuan University

In this paper,a set of fractional partial differential equations based on fractional total variation and fractional steepest descent approach are proposed to address the problem of traditional drawbacks of PM and ROF multi-scale denoising for texture *** extending Green,Gauss,Stokes and Euler-Lagrange formulas to fractional field,we can find that the integer formulas are just their special case of fractional *** order to improve the denoising capability,we proposed 4 fractional partial differential equation based multiscale denoising models,and then discussed their stabilities and convergence *** deduction and experimental evaluation demonstrate the stability and astringency of fractional steepest descent approach,and fractional nonlinearly multi-scale denoising capability and best value of parameters are discussed *** experiments results prove that the ability for preserving high-frequency edge and complex texture information of the proposed denoising models are obviously superior to traditional integral based algorithms,especially for texture detail rich images.

关键词： fractional Green formula fractional Euler-Lagrange equation fractional steepest descent approach fractional extreme points fractional total variation fractional differential mask.

Fractional Differential Amplitude Hierarchical Feature of MPSK Signals

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Fractional Differential Amplitude Hierarchical Feature of MP...

Fractional-order memristive neural synaptic weighting achieved by pulse-based fracmemristor bridge circuit

2006 8th International Conference on Signal Processing

作者： Wan Xiaoyu pu yifei Li Bingjun School of Electronics and Information Sichuan UniversityChengdu Chongqing University of Posts and Telecommunication School of Electronic Engineering University of Electronic Science and Technology of China School of Electronics and Information Sichuan University

ISBN: (纸本)9780780397361

＜正＞Fractional calculus signal can be regarded as generalized amplitude-phase *** amplitude changes with frequency as fractional power exponent while its phase changes with frequency as generalized Hilbert *** fractional differential is able to transiently detect and characterize M-ary phase shift keying（MPSK） *** paper implements special digital signal sequences to analyze the relationship between fractional differential amplitude hierarchical feature and the M value of MPSK signals and to study the relationship between the corresponding models of different phases and its fractional differential amplitude hierarchical feature in detail.

关键词： Fractional Calculus Amplitude Hierarchical Feature Generalized Amplitude-Phase Modulation Generalized Hilbert Transform Modulation Identification

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Frontiers of Information Technology & Electronic Engineering 2021年第6期22卷 862-876页

作者： yifei pu Bo YU Qiuyan HE Xiao YUAN College of Computer Science Sichuan UniversityChengdu 610065China School of Physics and Engineering Technology Chengdu Normal UniversityChengdu 611130China College of Electronics and Information Engineering Sichuan UniversityChengdu 610065China

We propose a novel circuit for the fractional-order memristive neural synaptic weighting(FMNSW).The introduced circuit is different from the majority of the previous integer-order approaches and offers important advantages. Since the concept of memristor has been generalized from the classic integer-order memristor to the fractional-order memristor(fracmemristor), a challenging theoretical problem would be whether the fracmemristor can be employed to implement the fractional-order memristive synapses or not. In this research, characteristics of the FMNSW, realized by a pulse-based fracmemristor bridge circuit, are investigated. First, the circuit configuration of the FMNSW is explained using a pulse-based fracmemristor bridge circuit. Second, the mathematical proof of the fractional-order learning capability of the FMNSW is analyzed. Finally, experimental work and analyses of the electrical characteristics of the FMNSW are presented. Strong ability of the FMNSW in explaining the cellular mechanisms that underlie learning and memory, which is superior to the traditional integer-order memristive neural synaptic weighting, is considered a major advantage for the proposed circuit.

关键词： Fractional calculus Fracmemristor Fracmemristance Fractional-order memristor Fractional-order memristive synapses

An Improved Task Scheduling Algorithm in Grid Computing Environment

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International Journal of Communications, Network and System Sciences 2011年第4期4卷 227-231页

作者： Liang Yu Gang Zhou yifei pu 不详

Algorithm research of task scheduling is one of the key techniques in grid computing. This paper firstly describes a DAG task scheduling model used in grid computing environment, secondly discusses generational scheduling (GS) and communication inclusion generational scheduling (CIGS) algorithms. Finally, an improved CIGS algorithm is proposed to use in grid computing environment, and it has been proved effectively.

关键词： Grid Computing Model of Task Scheduling Heuristics Algorithm Dependent Task Scheduling Algorithm

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非局部多尺度分数阶微分图像增强算法研究

电子与信息学报 2019年第12期41卷 2972-2979页

作者：黄果许黎陈庆利蒲亦非乐山师范学院互联网自然语言智能处理四川省高等学校重点实验室乐山614000 乐山师范学院物理与电子工程学院乐山614000 四川大学计算机科学学院成都610064

为了更好增强图像中的有用信息,改善图像视觉效果,该文提出了一种基于非局部多尺度分数阶微分图像增强算子(NMFD)。该算子首先将图像分成若干块子图像,计算每一块子图像的边缘强度系数、熵值和粗糙度等细节特征,将得到的特征数据在全局... 详细信息

为了更好增强图像中的有用信息,改善图像视觉效果,该文提出了一种基于非局部多尺度分数阶微分图像增强算子(NMFD)。该算子首先将图像分成若干块子图像,计算每一块子图像的边缘强度系数、熵值和粗糙度等细节特征,将得到的特征数据在全局图像范围进行统一尺度的归一化,然后对这些归一化的数据进行加权求和作为图像的非局部特征值,最后利用指数函数建立图像细节特征和分数阶微分算子阶次之间的非线性量化关系,在不同的图像子块区域,确定不同尺度的分数阶微分阶次,实现图像的非局部多尺度增强。

关键词：图像增强非局部多尺度分数阶微分算子图像熵值图像对比度

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DCT子空间的非局部均值去噪算法

计算机辅助设计与图形学学报 2012年第1期24卷 89-96页

作者：胡金蓉蒲亦非张意周激流四川大学计算机学院成都610064

在整个图像块像素灰度值向量空间中,非局部均值(nonlocal means,NLM)算法度量像素间的相似性不仅计算复杂度高,而且当噪声存在时还不能准确地计算出像素间的相似性权重值,影响了对图像冗余性质的利用,使得去噪结果图像对比度和清晰度低... 详细信息

在整个图像块像素灰度值向量空间中,非局部均值(nonlocal means,NLM)算法度量像素间的相似性不仅计算复杂度高,而且当噪声存在时还不能准确地计算出像素间的相似性权重值,影响了对图像冗余性质的利用,使得去噪结果图像对比度和清晰度低.针对NLM算法的这一缺陷,利用离散余弦变换(discrete cosine transform,DCT)的低数据相关性和高能量紧致性,将DCT与NLM算法相结合,对图像块进行DCT,并在DCT低频系数子空间内度量像素间的相似性.实验结果表明,与NLM算法相比,该方法能够在保护图像结构信息、对比度和清晰度的前提下更有效地去除噪声,峰值信噪比值一般可以提高1dB以上,运行时间不到NLM算法的1/10.

关键词：图像去噪非局部均值离散余弦变换能量紧致

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超级电容器恒流充电的时域分数阶电路模型

电工技术学报 2019年第17期34卷 3533-3541页

作者：余波梁锐蒲亦非杨果仁胡彧成都师范学院物理与工程技术学院成都611130 四川大学计算机学院成都610065

随着超级电容器作为新的储能装置得到广泛的应用,建立超级电容器的精确等效模型具有重要意义。根据分数阶微积分定义,结合分抗元的恒流充电曲线和超级电容器实际物理结构,直接在时域建立超级电容器恒流充电的分数阶RF串联电路模型和分数... 详细信息

随着超级电容器作为新的储能装置得到广泛的应用,建立超级电容器的精确等效模型具有重要意义。根据分数阶微积分定义,结合分抗元的恒流充电曲线和超级电容器实际物理结构,直接在时域建立超级电容器恒流充电的分数阶RF串联电路模型和分数阶RFR混联电路模型,并给出模型参数辨识与拟合误差分析方法。在结合超级电容器恒流充电数据完成分数阶RF串联电路模型和分数阶RFR混联电路模型的参数辨识与误差分析的过程中,发现分数阶RF串联电路模型和分数阶RFR混联电路模型的拟合精度均远优于一阶RC电路模型和经典等效电路模型,且这两种分数阶模型的精度相当。分析更简洁的分数阶RF串联电路模型的参数敏感性,得到模型中分抗元运算阶、分抗元特征值和电阻值对超级电容器恒流充电的影响规律。该文同时还说明经典等效电路模型是分数阶RFR混联电路模型的特殊情况,一阶RC电路模型是分数阶RF串联电路模型的特殊情况,分数阶RF串联电路模型是分数阶RFR混联电路模型的特殊情况。

关键词：超级电容器分数阶微积分等效电路模型分抗逼近电路

基于分数阶Riemann-Liouville积分的图像去噪

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计算机应用 2013年第1期33卷 35-39页

作者：黄果许黎陈庆利蒲亦非乐山师范学院智能信息处理及应用实验室四川乐山614000 乐山师范学院物理与电子工程学院四川乐山614000 四川大学计算机学院成都610064

为了在获得更好去噪性能的同时更多地保留图像纹理信息,介绍了分数阶Riemann-Liouville(R-L)积分算子在信号滤波中的作用,将分数阶R-L积分理论引入到数字图像去噪中,并利用阶梯逼近方法来实现数值计算。模型通过设定微小的积分阶次来构... 详细信息

为了在获得更好去噪性能的同时更多地保留图像纹理信息,介绍了分数阶Riemann-Liouville(R-L)积分算子在信号滤波中的作用,将分数阶R-L积分理论引入到数字图像去噪中,并利用阶梯逼近方法来实现数值计算。模型通过设定微小的积分阶次来构建相应的图像去噪掩模,由此实现噪声图像的局部微调,并利用迭代的思想来控制模型的去噪强度,从而获得较好的图像去噪效果。实验结果表明,基于分数阶R-L积分的图像去噪算法较传统的去噪方法不仅可以提高图像的信噪比(SNR),所提出的算法去噪后图像的信噪比为18.3497 dB,较传统去噪方法最低也提升了大约4%,而且可以更好地保留图像的弱边缘和纹理等细节信息。

关键词：分数阶Riemann—Liouville积分柯西公式迭代去噪掩模图像去噪阶梯逼近