提高光谱匹配精度的散射噪声消除方法
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摘要
光谱仪器采集光谱数据时,散射噪声会对光谱数据产生影响。同一种矿物质在不同颗粒度和浓度状态下的光谱数据曲线会产生偏移,进而降低光谱数据的匹配精度。针对这一问题,研究了基于多元散射校正融合增广拉格朗日消除光谱数据散射噪声和偏移的方法,先用该方法对光谱数据预处理进行校正,再结合光谱角方法进行相似度匹配测量。实验选取了6种矿物和6种壁画颜料作为光谱数据样本,使用光谱匹配方法分别对原光谱数据和消除散射噪声和偏移后的光谱数据进行匹配计算和分析。实验结果表明,使用多元散射校正融合增广拉格朗日方法消除散射噪声和偏移校正后的光谱数据匹配精度高于未校正的光谱数据,因此该方法可提高识别效果。
Scattering noise affects spectral data collected with spectral instruments.Spectral data curves measured for the same mineral species at different particle sizes and concentrations can produce an offset,which reduces the accuracy for matching the spectral data.To solve this problem,the present study reported a method based on the multi-scattering correction using merged augmented Lagrangian,in order to eliminate scattering noise and the resulting offset of spectral data;the method was firstly used accurate preprocessing,and then was used to similarity matching measurements combined with the spectral angles of the data.Six minerals and six pigments in the murals were selected as samples for the experiments.The spectral matching method was used to match and analyze the spectral data,which eliminated scattering noise and offset.Experimental results show that spectral data corrected using the proposed method are more accurately matched than uncorrected spectral data.In addition,the proposed method is more effective for mineral-species identification.
Scattering noise affects spectral data collected with spectral instruments.Spectral data curves measured for the same mineral species at different particle sizes and concentrations can produce an offset,which reduces the accuracy for matching the spectral data.To solve this problem,the present study reported a method based on the multi-scattering correction using merged augmented Lagrangian,in order to eliminate scattering noise and the resulting offset of spectral data;the method was firstly used accurate preprocessing,and then was used to similarity matching measurements combined with the spectral angles of the data.Six minerals and six pigments in the murals were selected as samples for the experiments.The spectral matching method was used to match and analyze the spectral data,which eliminated scattering noise and offset.Experimental results show that spectral data corrected using the proposed method are more accurately matched than uncorrected spectral data.In addition,the proposed method is more effective for mineral-species identification.
引文
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[19]Wang S L,Shang L P,Li Z F,et al.Multiplicative scatter correction in the application of fluorescence analysis[J].Journal of Light Scattering,2013,25(2):187-191.王顺利,尚丽平,李占锋,等.多元散射校正在荧光谱分析中的应用研究[J].光散射学报,2013,25(2):187-191.
[20]Wang D M,Ji J M,Gao H Z.The effect of MSCspectral pretreatment regions on near infrared spectroscopy calibration results[J].Spectroscopy and Spectral Analysis,2014,34(9):2387-2390.王动民,纪俊敏,高洪智.多元散射校正预处理波段对近红外光谱定标模型的影响[J].光谱学与光谱分析,2014,34(9):2387-2390.
[21]Du X P,Liu H,Chen H,et al.Research of satellite shape inversion matching algorithm based on photometric characteristic[J].Acta Optica Sinica,2016,36(8):0820001.杜小平,刘浩,陈杭,等.基于光度特性的卫星形状反演匹配算法研究[J].光学学报,2016,36(8):0820001.
[22]Wang K,Wang H Q,Long Y Q,et al.Spectral reflectance reconstruction based on dimension reduction regularization polynomials[J].Laser&Optoelectronics Progress,2018,55(5):053004.王可,王慧琴,龙艳群,等.基于降维正则化多项式的光谱反射率重建方法[J].激光与光电子学进展,2018,55(5):053004.
[23]Zhu W,Tai X C,Chan T.Augmented Lagrangian method for a mean curvature based image denoising model[J].Inverse Problems and Imaging,2013,7(4):1409-1432.
[2]Hao S C,Shi J L,Wang J G,et al.Study of paints and drawing techniques of fine brushwork Yunlong ripples painting in Qing dynasty[J].Spectroscopy&Spectral Analysis,2016,36(2):487-490.郝生财,施继龙,王纪刚,等.清代工笔云龙水波纹绘画颜料及技法研究[J].光谱学与光谱分析,2016,36(2):487-490.
[3]Wang L L,Li Z M,Ma Q L,et al.Non-destructive and in-situidentification of pigments in wall paintings using hyperspectral technology[J].Dunhuang Research,2015(3):122-128.王乐乐,李志敏,马清林,等.高光谱技术无损鉴定壁画颜料之研究---以西藏拉萨大昭寺壁画为例[J].敦煌研究,2015(3):122-128.
[4]Zhao X,Wang L Q.Progress in the analysis and conservation of cultural relics and artworks with fiber optic reflectance spectroscopy[J].Spectroscopy and Spectral Analysis,2017,37(1):21-26.赵星,王丽琴.光导纤维反射光谱法在文物、艺术品分析和保护中的进展[J].光谱学与光谱分析,2017,37(1):21-26.
[5]Li J F,Wan X X.Non-destructive identification of mineral pigments in ancient murals by visible spectroscopy[J].Spectroscopy and Spectral Analysis,2018,38(1):200-204.李俊锋,万晓霞.可见光谱法无损识别壁画文物矿物质颜料的研究[J].光谱学与光谱分析,2018,38(1):200-204.
[6]Padma S,Sanjeevi S.Jeffries Matusita based mixedmeasure for improved spectral matching in hyperspectral image analysis[J].International Journal of Applied Earth Observation and Geoinformation,2014,32:138-151.
[7]Wang W C,Wang H Q,Wang K,et al.An identification method of spectral information divergence pigment based on statistical manifold[J].Laser&Optoelectronics Progress,2018,55(1):013002.王伟超,王慧琴,王可,等.一种基于统计流形的光谱信息散度颜料识别方法[J].激光与光电子学进展,2018,55(1):013002.
[8]Wu F Q,Yang W N,Li D.Research on art painting pigment composition recognition based on spectra feature fitting[J].Journal of Light Scattering,2014,26(1):88-92.武锋强,杨武年,李丹.基于光谱特征拟合的艺术画颜料成分识别研究[J].光散射学报,2014,26(1):88-92.
[9]Shanmugam S,Perumal P S.Spectral matching approaches in hyperspectral image processing[J].International Journal of Remote Sensing,2014,35(24):8217-8251.
[10]Cui J,Dong X P,Wu Z X,et al.A high-precision method for determining the FBG peak wavelength shift based on FBG actual reflection spectrum match[J].Chinese Journal of Lasers,2011,38(7):0705001.崔剑,董小鹏,吴兆喜,等.基于FBG实际反射谱匹配的FBG峰值波长偏移量的高精度确定方法[J].中国激光,2011,38(7):0705001.
[11]Gao L,Zhu X C,Li C,et al.Improve the prediction accuracy of apple tree canopy nitrogen content through multiple scattering correction using spectroscopy[J].Agricultural Sciences,2016,7(10):651-659.
[12]Dieu V N,Ongsakul W.Augmented Lagrange Hopfield network based Lagrangian relaxation for unit commitment[J].International Journal of Electrical Power&Energy Systems,2011,33(3):522-530.
[13]Mou Y,You X G,Xu D Q,et al.Regularized multivariate scatter correction[J].Chemometrics and Intelligent Laboratory Systems,2014,132:168-174.
[14]Wang C L,Li Y S,Liu X W,et al.Phase error correction in Fourier transform spectrometer based on phase correlation[J].Journal of Applied Optics,2011,32(5):878-882.王彩玲,李玉山,刘学武,等.基于相位相关性的傅里叶变换光谱数据的相位误差修正方法[J].应用光学,2011,32(5):878-882.
[15]Antczak T.The exact absolute value penalty function method for identifying strict global minima of order m in nonconvex nonsmooth programming[J].Optimization Letters,2016,10(7):1561-1576.
[16]Chang X K.Augmented Lagrangian iteration method for convex quadratic SDP[J].Mathematica Numerica Sinica,2014,36(2):133-142.常小凯.二次半定规划的增广拉格朗日算法[J].计算数学,2014,36(2):133-142.
[17]Lei M,Li M,Ma X P,et al.Spectral scatter correction of coal samples based on quasi-linear local weighted method[J].Spectroscopy and Spectral Analysis,2014,34(7):1816-1820.雷萌,李明,马小平,等.基于拟线性局部加权法的煤样光谱散射校正[J].光谱学与光谱分析,2014,34(7):1816-1820.
[18]Liu Y,Luo W Q,Wang R D,et al.Sub-diffuse scattering of biological tissues and its application to spectroscopy[J].Chinese Journal of Lasers,2017,44(8):0807001.刘迎,罗雯倩,王汝丹,等.生物组织的亚扩散散射及其光谱技术的应用[J].中国激光,2017,44(8):0807001.
[19]Wang S L,Shang L P,Li Z F,et al.Multiplicative scatter correction in the application of fluorescence analysis[J].Journal of Light Scattering,2013,25(2):187-191.王顺利,尚丽平,李占锋,等.多元散射校正在荧光谱分析中的应用研究[J].光散射学报,2013,25(2):187-191.
[20]Wang D M,Ji J M,Gao H Z.The effect of MSCspectral pretreatment regions on near infrared spectroscopy calibration results[J].Spectroscopy and Spectral Analysis,2014,34(9):2387-2390.王动民,纪俊敏,高洪智.多元散射校正预处理波段对近红外光谱定标模型的影响[J].光谱学与光谱分析,2014,34(9):2387-2390.
[21]Du X P,Liu H,Chen H,et al.Research of satellite shape inversion matching algorithm based on photometric characteristic[J].Acta Optica Sinica,2016,36(8):0820001.杜小平,刘浩,陈杭,等.基于光度特性的卫星形状反演匹配算法研究[J].光学学报,2016,36(8):0820001.
[22]Wang K,Wang H Q,Long Y Q,et al.Spectral reflectance reconstruction based on dimension reduction regularization polynomials[J].Laser&Optoelectronics Progress,2018,55(5):053004.王可,王慧琴,龙艳群,等.基于降维正则化多项式的光谱反射率重建方法[J].激光与光电子学进展,2018,55(5):053004.
[23]Zhu W,Tai X C,Chan T.Augmented Lagrangian method for a mean curvature based image denoising model[J].Inverse Problems and Imaging,2013,7(4):1409-1432.