一种EMD的SAR图像自适应辐射均衡方法
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摘要
针对合成孔径雷达(synthetic aperture radar,SAR)侧视观测模式及天线方向图引起的SAR图像辐射差异严重影响SAR图像的广泛应用问题,根据经验模态分解(empirical mode decomposition,EMD)技术的自适应、自驱动和多尺度等特性,提出了基于EMD技术的SAR图像自适应辐射均衡方法。该方法利用EMD技术获取SAR图像距离向的多阶本征模函数,自适应地确定包含辐射误差的低频信息,并将其优化可获得辐射误差趋势信息和补偿因子,从而均衡SAR图像。将该方法应用到已知误差趋势的仿真数据以及多组机载SAR真实数据,结果表明该方法能够有效地自适应补偿SAR图像的辐射差异,提高了SAR图像的可视化效果和解译能力。
To solve the problem that the application of synthetic aperture radar(SAR)image is seriously affected by its radiation differences which result from SAR side-looking mode and the antenna pattern,based on empirical mode decomposition(EMD)technique of adaptive,self-driven and multi-scale features,this paper proposes the SAR image adaptive radiation balance method based on the EMD technique.Firstly,by using the technology of EMD,it gains the intrinsic mode function(IMF)of SAR image's range directions.Next,it adaptively determines the low frequency containing background radiation error.Then,by smoothing the trend information it obtains compensation factor.Finally,it realizes the balance of the SAR image.With a known radiation difference of simulation data and multiple sets of airborne SAR real data to do the experiment.The results show that the method can efficiently and adaptively make up for the radiation difference of the SAR image,and improve the visualization and interpretation skills of the SAR image.
To solve the problem that the application of synthetic aperture radar(SAR)image is seriously affected by its radiation differences which result from SAR side-looking mode and the antenna pattern,based on empirical mode decomposition(EMD)technique of adaptive,self-driven and multi-scale features,this paper proposes the SAR image adaptive radiation balance method based on the EMD technique.Firstly,by using the technology of EMD,it gains the intrinsic mode function(IMF)of SAR image's range directions.Next,it adaptively determines the low frequency containing background radiation error.Then,by smoothing the trend information it obtains compensation factor.Finally,it realizes the balance of the SAR image.With a known radiation difference of simulation data and multiple sets of airborne SAR real data to do the experiment.The results show that the method can efficiently and adaptively make up for the radiation difference of the SAR image,and improve the visualization and interpretation skills of the SAR image.
引文
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[17]王文波,赵攀,张晓东.利用经验模态分解和主成分分析的SAR图像相干斑抑制[J].测绘学报,2012,41(6):838-843.
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[20]HUANG N E,SHEN Z,LONG S R,et al.The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[J].Proceedings of the Royal Society of London,1998,454(1971):903-995.
[21]KABIR M A,SHAHNAZ C.Denoising of ECG signals based on noise reduction algorithms in EMD and wavelet domains[J].Biomedical Signal Processing and Control,2012,7(5):481-489.
[22]MO J,HU W,LE S.Improving empirical mode decomposition based on up-sampling[C]//2014IEEE/ACIS 13th International Conference on Computer and Information Science(ICIS),2014:425-428.
[23]岳廷明,王金海,王慧泉.融合加速度信息的动态心电EMD滤波算法[J].计算机工程与应用,2015,51(20):192-197.
[24]何经纬.基于EMD的包络相关算法研究[D].广西:广西师范大学,2015.
[25]ZHANG Y,LIU X,LI H F.Self-adaptive image histogram equalization algorithm[J].Journal of Zhejiang University:Engineering Science,2007,41(4):630-633.
[26]XIE Z X,WANG Z F,LIU Y H,et al.A Method acquiring the best image in lower layer image mining:China,CN101419707A[P].2009-04-29.
[27]孟天佑,汪云甲.遥感图像理想均衡化及图像质量定量评价[J].中国图象图形学报,2012,17(5):729-739.
[28]LIAO Q N.New color image encryption and decryption algorithm[J].Computer Engineering,2010,36(17):144-146.
[2]陈尔学.星载合成孔径雷达影像正射方法研究[D].北京:中国林业科学研究院,2004.
[3]王晓宁,卢鹏,徐天蜀.多山地区合成孔径雷达数据预处理方法[J].云南地理环境研究,2014,26(6):61-65.
[4] BREIT H,FRITZ T,BALSS U,et al.Terra SAR-X SAR processing and products[J].IEEE T Geosci Remote,2010,48(2):727-740.
[5]云日升,郭伟,魏茉.亚马逊热带雨林星载SAR辐射定标算法[J].雷达科学与技术,2007(2):139-143,148.
[6]王一丁,涂国防,洪峻.SAR辐射定标中的地物杂波抑制方法[J].遥感学报,2005,9(5):544-548.
[7]陶鹍,张云华,郭伟,等.星载SAR亚马逊雨林辐射定标仿真研究[J].空间科学学报,2006(4):309-314.
[8]云日升,郭伟.亚马逊热带雨林星载SAR天线方向图获取与应用[J].测试技术学报,2008,22(4):301-306.
[9]岳焕印,郭华东,韩春明,等.经验模态分解技术在SAR干涉图滤波中的应用[J].高技术通讯,2001(12):37-40.
[10]韩春明.SAR图像斑点滤波研究[D].北京:中国科学院研究生院(遥感应用研究所),2003.
[11]MARIA B B,GUSTAVO E G,ALEJANDRO F A,et al.Evaluation of the 1Dempirical mode decomposition method to smooth digital speckle pattern interferometry fringes[J].Optics and Lasers in Engineering,2007,45:723-729.
[12]燕琴,靳国旺,张继贤,等.天线方向图未知的机载SAR图像增强[J].测绘学报,2013,42(4):554-558.
[13]KARUNESH K,GUPTA R G.An algorithm for road enhancement in SAR images using wavelet transform[J].Journal of the Indian Society of Remote Sensing,2007,35(4):361-367.
[14]DEERING R,KAISER J F.The use of a masking signal to improve empirical mode decomposition[J].IEEE ICASSP,Philadelphia,USA,2005,4:485-488.
[15]李夕兵,张义平,左宇军,等.岩石爆破振动信号的EMD滤波与消噪[J].中南大学学报,2006,37(1):150-154.
[16]王婷.EMD算法研究及其在信号去噪中的应用[D].吉林:哈尔滨工程大学,2010.
[17]王文波,赵攀,张晓东.利用经验模态分解和主成分分析的SAR图像相干斑抑制[J].测绘学报,2012,41(6):838-843.
[18]DAVID L,DANILO P M.Multiscale image fusion using complex extensions of EMD[J].IEEE Transactions on Signal Processing,2009,57(4):1627-1630.
[19]KOPSINIS Y,MCLAUGHLI S.Development of EMD Based Denoising Methods Inspired by Wavelet Thresholding[J].IEEE Transactions on Signal Processing,2009,54(4)1351-1362.
[20]HUANG N E,SHEN Z,LONG S R,et al.The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[J].Proceedings of the Royal Society of London,1998,454(1971):903-995.
[21]KABIR M A,SHAHNAZ C.Denoising of ECG signals based on noise reduction algorithms in EMD and wavelet domains[J].Biomedical Signal Processing and Control,2012,7(5):481-489.
[22]MO J,HU W,LE S.Improving empirical mode decomposition based on up-sampling[C]//2014IEEE/ACIS 13th International Conference on Computer and Information Science(ICIS),2014:425-428.
[23]岳廷明,王金海,王慧泉.融合加速度信息的动态心电EMD滤波算法[J].计算机工程与应用,2015,51(20):192-197.
[24]何经纬.基于EMD的包络相关算法研究[D].广西:广西师范大学,2015.
[25]ZHANG Y,LIU X,LI H F.Self-adaptive image histogram equalization algorithm[J].Journal of Zhejiang University:Engineering Science,2007,41(4):630-633.
[26]XIE Z X,WANG Z F,LIU Y H,et al.A Method acquiring the best image in lower layer image mining:China,CN101419707A[P].2009-04-29.
[27]孟天佑,汪云甲.遥感图像理想均衡化及图像质量定量评价[J].中国图象图形学报,2012,17(5):729-739.
[28]LIAO Q N.New color image encryption and decryption algorithm[J].Computer Engineering,2010,36(17):144-146.