基于均值滤波矩阵组的二维信号快速经验模式分解方法

doi:10.3969/j.issn.0372-2112.2012.10.013

电子学报 ›› 2012, Vol. 40 ›› Issue (10): 1980-1983.DOI: 10.3969/j.issn.0372-2112.2012.10.013

基于均值滤波矩阵组的二维信号快速经验模式分解方法

郭珈^1,2, 王孝通^2,3, 徐晓刚^2,4, 张成堡⁵

1. 海军91550部队, 辽宁大连 116023;
2. 海军大连舰艇学院光电技术研究所, 辽宁大连 116018;
3. 海军大连舰艇学院航海系, 辽宁大连 116018;
4. 海军大连舰艇学院装备系统与自动化系, 辽宁大连 116018;
5. 海军32132部队, 山东青岛 266405

收稿日期:2011-07-18 修回日期:2012-08-25 出版日期:2012-10-25
- 作者简介:
- 郭珈 女,1983年8月出生于辽宁大连市,现为海军91550部队工程师、博士.研究方向为图像视频处理. E-mail:guojia828@163.com 王孝通 男,1962年3月出生于浙江义乌,现为海军大连舰艇学院航海系教授、博士后、博士生导师.研究方向为信号分析、图像处理、电子海图等. E-mail:dljtxywxt@163.com
- 基金资助:
- 国家自然科学基金 (No.60975016); 青年科学基金 (No.61002052); 辽宁省自然科学基金 (No.20082176)

Fast 2D Empirical Mode Decomposition Based on Mean Value Matrix Filter Sets

GUO Jia^1,2, WANG Xiao-tong^2,3, XU Xiao-gang^2,4, ZHANG Cheng-bao⁵

1. Unit 91550, Dalian, Liaoning 116023, China;
2. Institute of Photoelectric Technology, Dalian Naval Academy, Dalian, Liaoning 116018, China;
3. Department of Navigation, Dalian Naval Academy, Dalian, Liaoning 116018, China;
4. Department of Automatization, Dalian Naval Academy, Dalian, Liaoning 116018, China;
5. Unit 92132, Qingdao, Shandong 266405, China

Received:2011-07-18 Revised:2012-08-25 Online:2012-10-25 Published:2012-10-25
- Supported by:
- National Natural Science Foundation of China (No.60975016); Youth Fund of National Natural Science Foundation of China (No.61002052); Natural Science Foundation of Liaoning Province, China (No.20082176)

摘要/Abstract

摘要： 根据矩阵变换理论,提出了一种基于滤波矩阵组的局部均值求取方法.该方法构造了均值滤波矩阵组,只需在待处理矩阵左右各乘一个均值滤波阵,即可得到待处理阵的加权均值,简化了包络均值求解过程.在上述局部均值滤波理论的基础上,提出了二维信号的快速经验模式分解算法.实验证明,算法运算时间比传统经验模式分解方法提高了两到三个数量级.

关键词: 经验模式分解(EMD)快速算法, 均值滤波矩阵, 图像融合

Abstract: A new local mean value computing algorithm is proposed based on the theory of the mean value matrix filter sets.The algorithm computes the weighted mean value of the matrix by multiplying a mean value filter matrix to each side of it.This special matrix can be calculated quickly and simplify the process of envelope computing.Based on the mean value matrix filter sets,a fast two-dimension EMD algorithm is proposed.Experiments show this algorithm works well on image fusion.It can also reduce the computation time by 1/100~1/1000 than that of the traditional EMD.

Key words: fast algorithm of empirical mode decomposition (EMD), mean value filter matrix, image fusion

中图分类号:

TP391

郭珈, 王孝通, 徐晓刚, 张成堡. 基于均值滤波矩阵组的二维信号快速经验模式分解方法[J]. 电子学报, 2012, 40(10): 1980-1983.

GUO Jia, WANG Xiao-tong, XU Xiao-gang, ZHANG Cheng-bao. Fast 2D Empirical Mode Decomposition Based on Mean Value Matrix Filter Sets[J]. Acta Electronica Sinica, 2012, 40(10): 1980-1983.

参考文献

[1] Huang N E,Zheng S,Steven R L,et al.The empirical mode decomposition and the Hilbert spectrum for non-linear non-stationary time series analysis [J].Proc R Soc London Ser A,1998,454:903-995.
[2] Rutkowskitm T M,Mandic D P,Cichocki A,et al.EMD approach to multichannel EEG data —The amplitude and phase components clustering analysis [J].Journal of Circuits,Systems and Computers,2010,19(1):215-229.
[3] Looneyd,Mandic D P.Multiscale image fusion using complex extensions of EMD [J].IEEE Transactions on Signal Processing,2009,57(4):1626-1630.
[4] Rehan N,Mandic D P.Multivariate empirical mode decomposition [J].Proc R Soc A,2010,466(2117):1291-1302.
[5] 徐晓刚,徐冠雷,王孝通,等.经验模式分解(EMD)及其应用[J].电子学报,2009,37(3):581-585. XU Xiao-gang,XU Guan-lei,WANG Xiao-tong,et al.Empirical mode decomposition and its application [J].Acta Electronica Sinica,2009,37(3):581-585.(in Chinese)
[6] Han C M,Guo H D,Wang C,et al.A novel method to reduce speckle in SAR images.International Journal of Remote Sensing,2002,23(23):5095-5101.
[7] Yue H Y,Guo H D,Han C M,et al.A SAR interferogram filter based on the empirical mode decomposition method.Proceedings of IGARSS 2001:Geoscience and Remote Sensing Symposium.New York:IEEE,2001.2061-2063.
[8] Nunes J C,Bouaoune Y,Delechlle E,et al.Texture analysis based on the bidimensional empirical mode decomposition with gray-Level co-occurrence models [J].Machine Vision and Application,2003,2:633-635.
[9] Yang Zhihua,Qi Dongxu,Yang Lihua.Signal period analysis based on Hilbert-Huang Transform and its application to texture analysis [A].Proceedings of the Third International Conference on Image and Graphics [C].Washington DC:IEEE,2004.430-433.
[10] Xiong Changzhen,Xu Junyi,Zou Jiancheng,et al.Texture classification based on EMD and FFT[J].Zhejiang Univ Sci(A),2006,7(9):1516-1521.
[11] Nunes J C,Guyot S,Delechlle E.Texture analysis based on local analysis of the bidimensional empirical mode decomposition[J].Machine Vision and Applications,2005,16:177-188.
[12] Xu Guanlei,Wang Xiaotong,Xu Xiaogang.Multi-band image fusion algorithm based on neighborhood limited empirical mode decomposition [J].Journal of Infrared and Millimeter Waves.2006,25(3):225-228.
[13] 徐冠雷,王孝通,徐晓刚等.基于限邻域EMD的图像增强[J].电子学报,2009,34(9):1635-1639. XU Guan-lei,WANG Xiao-tong,XU Xiao-gang,et al.Image enhancement algorithm based on neighborhood limited empirical mode decomposition [J].Acta Electronica Sinica,2009,34(9):1635-1639.(in Chinese)
[14] Xu Guanlei,Wang Xiaotong,Xu Xiaogang.Improved bi-dimensional empirical mode decomposition based on 2D assisted signals:Analysis and application [J].IET Image Processing,2011,5(3):205-211.

[1]	徐少平, 林珍玉, 张贵珍, 陈孝国, 李芬. 采用深度学习与图像融合混合实现策略的低照度图像增强算法[J]. 电子学报, 2021, 49(1): 72-76.
[2]	秦福强, 王丽芳. 基于变分的多尺度遥感图像融合算法[J]. 电子学报, 2020, 48(6): 1084-1090.
[3]	邓立暖, 尧新峰. 基于NSST的红外与可见光图像融合算法[J]. 电子学报, 2017, 45(12): 2965-2970.
[4]	戴文战, 姜晓丽, 李俊峰. 基于人眼视觉特性的NSCT医学图像自适应融合[J]. 电子学报, 2016, 44(8): 1932-1939.
[5]	刘斌, 刘维杰, 罗益辉, 郭琳. 八通道MSVD构造及其在多聚焦图像融合中的应用[J]. 电子学报, 2016, 44(7): 1694-1701.
[6]	闫利, 向天烛. NSCT域内结合边缘特征和自适应PCNN的红外与可见光图像融合[J]. 电子学报, 2016, 44(4): 761-766.
[7]	涂超平, 肖进胜, 杜康华, 易本顺. 基于各向异性热扩散方程的多聚焦图像融合算法[J]. 电子学报, 2015, 43(6): 1192-1199.
[8]	李奕, 吴小俊. 粒子群进化学习自适应双通道脉冲耦合神经网络图像融合方法研究[J]. 电子学报, 2014, 42(2): 217-222.
[9]	刘斌, 祝青, 胡福强, 刘维杰. 基于采样二通道不可分小波的多光谱图像融合[J]. 电子学报, 2013, 41(4): 710-716.
[10]	卢振坤, 玉振明. 基于自适应局部Log-Gabor能量的多聚焦图像融合[J]. 电子学报, 2013, 41(1): 199-204.
[11]	马苗, 万仁远, 尹义龙. 基于相似性灰关联的Curvelet域多聚焦图像融合[J]. 电子学报, 2012, 40(10): 1984-1988.
[12]	刘斌;彭嘉雄. 基于非下采样三通道不可分对称小波的多光谱图像融合[J]. 电子学报, 2011, 39(5): 1094-1099.
[13]	高雪妮;玉振明;张军;李陶深. 基于多级分块迭代法的不同聚焦图像融合[J]. 电子学报, 2011, 39(3): 690-694.
[14]	李光鑫;徐抒岩;董吉洪. 结构优化型颜色传递融合方法[J]. 电子学报, 2011, 39(1): 213-218.
[15]	胡根生;梁栋;孔颉. 基于支持向量值轮廓波变换的遥感影像融合[J]. 电子学报, 2010, 38(6): 1287-1292.

基于均值滤波矩阵组的二维信号快速经验模式分解方法

Fast 2D Empirical Mode Decomposition Based on Mean Value Matrix Filter Sets

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics