Hyperspectral estimation of soil organic matter based on different spectral preprocessing techniques

In this study, the potentiality of visible and near-infrared reflectance spectroscopy to estimate soil organic matter was assessed. Six preprocessing methods were implemented to process the original spectra. The partial least-squares regression approach was also applied to construct predictive models and evaluate the optimal spectral preprocessing method. The significant wavelengths of soil organic matter were determined by using the correlation analysis and the partial least-squares regression analysis. The results were: (i) visible and near-infrared reflectance spectroscopy was proved to be an ideal approach in the soil organic matter estimation; (ii) different preprocessed spectra could improve their correlation with soil organic matter; the combination of first-order derivative and Savitzky–Golay smoothing method outperformed other preprocessing methods; (iii) the soil organic matter predictive models based on spectra processed by derivatives and Savitzky–Golay smoothing together presented a satisfactory accuracy, yielding the determination coefficient and root mean square error values of 0.986 and 0.077, respectively, for first-order derivative; and 0.973 and 0.105, respectively, for second-order derivative. The combination of first-order derivative and Savitzky–Golay smoothing was ultimately recommended the preferable preprocessing method; and (iv) the wavelengths of 417, 1853, 1000, and 2412?nm were determined as the significant wavelengths associated with soil organic matter. The study will provide a reference for the site specific management of agricultural inputs by using the visible and near-infrared reflectance spectroscopy technology.     

Determination of electron energy probability function in low-temperature plasmas from current – Voltage characteristics of two Langmuir probes filtered by Savitzky–Golay and Blackman window methods

Acceptable data for electron energy probability function (EEPF) measurement in low-pressure plasmas require a small depletion in near-zero electron energy and a large dynamic range in the high-energy regime. The voltage drop across internal resistance and noise from the data acquisition system cause a rounding of the EEPF near the zero electron energy and a reduction in the dynamic range due to a low signal-to-noise ratio of the high-energy regime, respectively, leading to erroneous interpretation in the EEPF measurement. A digital smoothing filter can be employed to reduce the noise signal, but it can also cause additional depletion near the zero energy. In order to obtain reliable EEPF data, a novel technique is proposed using two Langmuir probes with differing collecting areas and the Savitzky–Golay and Blackman window methods. The technique enables the internal resistance effect to be removed using a slope of the current – voltage characteristic taken from the probes. In addition, the Savitzky–Golay and Blackman window methods in the technique apply separately to two regimes of the EEPF, i.e., the near-zero energy regime and the inelastic energy regime, because appropriate smoothing methods that minimize loss and distortion of information differ for the two regimes. This allows one to decrease the noise signal, minimizing the additional depletion near the zero energy. This technique improves the dynamic range of the EEPF from 30 to 55 dB to 65–105 dB and provides more accurate electron density and effective electron temperature from the EEPF, compared to those of the conventional technique.     

Noise reduction in Raman spectra: Finite impulse response filtration versus Savitzky–Golay smoothing

Application of the finite impulse response (FIR) filtration technique for the removal of spectral noise and background broadband deformations from the Raman spectra is tested. Optimal parameters of FIR filters are found and their effectiveness is compared with the Savitzky–Golay (SG) smoothing procedure. The FIR filtration is found to be an effective procedure to treat the whole Raman spectra, but high computing power is needed. Copyright © 2007 John Wiley & Sons, Ltd.     

EEDF Determination by Numerical Processing of the Probe Data in Neon DC Discharge

Numerical processing of the data from single probe measurements allows determination of the electron energy distribution function (EEDF) from the second derivative of the probe current. The current‐voltage probe characteristics are measured by acquisition system for further smoothing and differentiation. The developed procedure is a combination of the Savitzky‐Golay (S‐G) smoothing filter and three‐point differentiator with varying step. The above methods are modified for irregularly sampled data which enables more accurate determination of EEDF. Advantages of this approach are data smoothing with minimum information loss and improved noise reduction at the differentiation procedure. The procedure is applied for EEDF calculation in low current low pressure neon discharge. The shape of EEDF shows deviation from both Maxwellian and Druyvesteyn distributions. (© 2006 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

上海城市植被光谱反射特征分析

地物光谱特征是遥感机理的重要内容,也是遥感应用研究的重要依据。城市植被作为城市中重要的生命支持系统,对于维持城市生态系统平衡起着核心的作用。文章以上海城市植被为研究对象,利用美国ASD公司生产的FieldSpec3便携式地物波谱仪,通过对2009年10月金边黄杨,金丝桃,圆柏,麦冬,珊瑚树,小叶黄杨等野外和室内光谱数据采集和处理,获得了这6种城市植被的高光谱数据。采用Savitzky Go-lay平滑方法进行光谱噪声去除和利用微分光谱技术进行植被环境背景影响消除,分别从植被冠层光谱和叶片光谱以及微分光谱,对这6种城市植被的光谱特征以及光谱曲线的差异和变化规律进行分析。可为今后进一步研究城市植被理化性能、参数反演、植被分类、植被调查以及城市环境监测等遥感应用服务。     

Accuracy of spectrum estimate in fluorescence spectral microscopy with spectral filters

We establish the accuracy of the spectrum that is estimated with an inexpensive fluorescence spectral microscope utilizing a small set of spectral filters [Soriano et al, Opt. Exp. 10, 1458–1464 (2002)]. The spectrum at an arbitrary image location of the fluorescent sample is estimated as a linear superposition of basis spectra that are derived by singular value decomposition (SVD) or principal component analysis (PCA) from a spectral library of fluorescence spectra. Estimation performance is analyzed as a function of library statistics, filter selection and sequencing, minimum negativity constraint and signal to noise ratio (SNR) of fluorescence image. We consider image SNR degradations that arise from weakening of image intensity, additive Gaussian noise, intensity-dependent Poisson noise and quantization errors. The recovery of specific spectral features like spectral resolution, general similarity and peak alignments, is assessed using Linfoot’s criteria of fidelity, structural content, and correlation. We found that estimation with SVD basis spectra is more robust against image noise than that with PCA basis spectra. However for high SNR images, accurate estimation is achieved more quickly with PCA basis spectra and with better response to the application of minimum negativity constraint.     

近红外光谱技术快速鉴别蜂胶品种的可行性研究

不同植物源的蜂胶物质组成不同,其生理和药理活性也存在着一定的差异。目前主要是根据蜂胶中物质组成及其含量的不同来鉴别蜂胶植物源,存在着一些局限性。因此,建立一种快速、准确鉴别蜂胶植物源的方法具有重要的意义。以三种不同植物源的蜂胶(杨树型蜂胶、桦树型蜂胶和橡树型蜂胶)为研究对象,利用傅里叶变换近红外光谱仪对蜂胶的无水乙醇溶液进行光谱扫描,采用主成分分析结合马氏距离判别法和典型判别分析分别建立蜂胶品种的判别模型并对其性能进行检验。结果表明： 在经过光谱预处理和主成分分析后,得到最佳的光谱建模波段为4 500～12 000 cm-1,最佳的光谱预处理方法为一阶导数+Savitzky-Golay(7)平滑;主成分分析结合马氏距离判别法建立的判别模型校正集和检验集的判别准确率分别为93.62%和82.61%;典型判别分析建立的判别模型的判别准确率为91.4%,交叉检验的判别准确率为88.6%。由此可知,主成分分析结合马氏距离判别法与典型判别分析对蜂胶样品的分类效果均较好。近红外光谱技术结合化学计量学方法应用于蜂胶植物源的快速、准确鉴别具有一定的可行性和实用性。     

一种基于连续小波变换的LIBS光谱自动寻峰方法

谱线寻峰在激光诱导击穿光谱(laser-induced breakdown spectroscopy)中是必不可少的步骤,然而噪声和背景的存在,干扰了寻峰的准确性。为了提高LIBS寻峰中重叠峰分辨能力和自适应能力,提出一种适用于LIBS谱图的自动寻峰方法。将基于连续小波变换的脊线寻峰法引入到LIBS中,探讨了连续小波变换中的小波母函数的选择并优化了尺度参数和平移参数,提出一套脊线校正方法对脊线寻峰法进行了改进。实验结果表明,该方法与直接比较法、导数法和脊线寻峰法相比,在重叠峰分辨能力和寻峰精度等方面优势显著,可应用于LIBS数据处理。     

小波包熵的复杂体系近红外光谱信息提取

有用信息提取是复杂体系近红外检测的重点和难点之一。由于复杂体系光谱中存在各种噪声、基线漂移、谱带重叠及复杂背景的干扰,常规方法不能准确地从光谱中获得有用信息。为此,将小波包变换(DWPT)和信息熵理论相结合--小波包熵(EWPIE)提取复杂体系光谱中的有用信息。思路是采用小波包变换对光谱信号进行多频带分解,根据有用信号与噪声的频带分布特点,基于信息熵理论滤除干扰的频率分量,采用正交校正法(OSC)剔除与被测组分无关的信息,然后对处理后的频率分量进行重构,从而实现复杂体系有用信息的准确提取。通过对复杂体系光谱数据建立多元校正模型来验证该方法的效果。采用牛奶的近红外光谱数据,以牛奶中脂肪和蛋白质浓度为研究对象,建立了偏最小二乘法(PLS)模型。结果显示,牛奶中脂肪和蛋白质的预测均方根误差(RMSEP)分别为0.132%和0.121%,与单纯的DWPT和OSC相比,EWPIE能够有效地提取有用信息,避免了无用信息的干扰,明显提高了模型的预测精度,对复杂体系的准确检测具有一定的理论意义和实际应用价值。     

Immunity of a Detection System for Optimum Space Filtration and Use of an Interference Compensator

The paper studies the dependence of the potential noise immunity of a detection system and noise immunity of a detection system with an interference compensator on the array parameters, angular signal position and local noise, the degree of correlation of distributed noise and spectral densities of the signal power, noise, and interference. The gain in noise immunity of the detection system when the optimal spatial filter is used with respect to the use of an interference compensator is estimated as a function of the degree of correlation of distributed noise and the power of random amplitude–phase errors of the weight coefficients of the array.     

光谱导数Kaiman滤波同时测定苯酚-邻氯苯酚和2，4二氯苯酚

文中提出了一个新的、稳定的光谱导数Kalman滤波紫外分光光度法同时定量分析方法，并且成功地将其应用于极难分辨的苯酚一邻氯苯酚和2，4二氯苯酚三组分混合体系的同时测量。选择分析光谱导数的原因是其不仅包含着吸光度，还包括在指定波长位置变化趋向等更多的信息量，这样更利于在吸收峰重叠的位置捕捉有较大差异的信号。利用Kalman滤波可以解决由光谱导数而引起的噪声放大问题，也可以过滤源于实验的噪声以及来自传递模型误差。在260-290nm区间测量了30组浓度各自在1～10mg·L^-1范围的苯酚一邻氯苯酚和2，4二氯苯酚标准混合溶液紫外吸收光谱图。利用分段延伸高次多项式回归模拟求导准确获得吸光度导数，并且利用偏最小二乘法将其制作成Kalman滤波标准工作系数矩阵。通过随机线性离散系统的Kalman滤波器最优平滑计算，对混合体系中的各组分进行定量分析。回收实验显示出，光谱导数Kalman滤波分析法应用于本实验的极难分辨的三组分体系，得到了非常高的回收率，并且在整个实验范围内光谱导数Kalman滤波分析法具有非常好的稳定性。     

基于加权LoG算子的红外弱小目标检测方法研究

提出一种基于加权LoG算子及形态学运算的方法来提高远距离红外弱目标检测效率。通过不同尺度的加权LoG算子对图像进行运算,提取响应值最大的特征图。对图像进行形态学运算去噪,并进行Otsu二值分割聚类。输出目标点在图像上的位置坐标。实验结果表明:该方法与传统滤波方法相比,信噪比增益为36.9,杂波抑制因子为4.7,均比传统滤波方法要好。     

Time-delay estimation of reverberated speech exploiting harmonic structure.

The relative time delay associated with a speech signal received at a pair of spatially separated microphones is a key component in talker localization and microphone array beamforming procedures. The traditional method for estimating this parameter utilizes the generalized cross correlation (GCC), the performance of which is compromised by the presence of room reverberations and background noise. Typically, the GCC filtering criteria used are either focused on the signal degradations due to additive noise or those due exclusively to multipath channel effects. There has been relatively little success at applying GCC weighting schemes which are robust to both of these conditions. This paper details an alternative approach which attempts to employ a signal-dependent criterion, namely, the estimated periodicity of the speech signal, to design a GCC filter appropriate for the combination of noise and multipath distortions. Simulations are performed across a range of room conditions to illustrate the utility of the proposed time-delay estimation method relative to conventional GCC filtering approaches.     

Laser spectroscopic oxygen sensor using diffuse reflector based optical cell and advanced signal processing

In this paper, an improved signal processing method is given, aiming at a sensitivity improvement of the tunable diode laser spectroscopy based gas concentration measurement. The gas absorption spectrum is probed with an optimum wavelength scanning function which enables a more efficient curve fit than for traditional linear wavelength scanning. The wavelength scanning function is determined to be optimum, in the sense that the variance of the estimated concentration noise is minimized. This optimum scanning function depends on the signal model used in curve fitting. Several models including interfering gas spectra and etalon fringes are examined. Compared to the gas absorption spectrum recorded by ramping the wavelength linearly, the optimum spectrum waveforms have a cascade structure, which means that the optimum scanning preferably samples important points of the spectrum. The new method theoretically enables a factor of ∼2 improvement on detection sensitivity of the estimated concentration. Furthermore, direct spectroscopy is superior to second harmonic detection, because the concentration noise can be an additional factor of ∼2 lower.     

基于三维荧光导数光谱的水体有机污染物浓度检测

提出了应用三维荧光一阶导数光谱检测水体中有机污染物浓度的分析方法。在计算三维荧光导数光谱时,采用Savitzky-Golay多项式拟合微分法对激发、发射光谱分别求导。由于在计算导数光谱时所采用的多项式拟合本身具有平滑功能,因此不需要单独进行平滑处理以去除噪声。针对所构成的四维荧光导数光谱(激发波长,发射波长,激发波长的一阶导数,发射波长的一阶导数),采用偏最小二乘方法建立回归模型。实验结果表明,在对水体中总有机碳的检测中,与常规的三维荧光光谱分析方法相比,文章提出的分析方法可较好地提高分析精度。     

Detection of partially filled gaps in noise and the temporal modulation transfer function

Results of experiments on the detection of silent intervals, or gaps, in broadband noise are reported for normal-hearing listeners. In some preliminary experiments, a gap threshold of about 2 ms was measured. This value was independent of the duration of the noise burst, variation of the noise level on each presentation, or the temporal position of the gap within the noise burst. In the main experiments, the thresholds for partial decrements in the noise waveform as well as brief increments were determined. As predicted by a model that assumes a single fixed peak-to-valley detection ratio, thresholds for increments are slightly higher than thresholds for decrements when the signal is measured as the change in rms noise level. A first-order model describes the temporal properties of the auditory system as a low-pass filter with a 7- to 8-ms time constant. Temporal modulation transfer functions were determined for the same subjects, and the estimated temporal parameters agreed well with those estimated from the gap detection data. More detailed modeling was carried out by simulating Viemeister's three-stage temporal model. Simulations, using an initial stage bandwidth of 4000 Hz and a 3-ms time constant for the low-pass filter, generate data that are very similar to those obtained from human subjects in both modulation and gap detection.     

基于匹配追踪的拉曼光谱信号重构算法

拉曼光谱技术是一种高灵敏度、无损伤、振动分子光谱技术,在医药、生物、分析化学等诸多领域有着重要的作用。然而,由于拉曼散射强度低,实际测得的拉曼信号容易被噪声所污染。特别是在较短的曝光时间,收集到的拉曼光谱的信噪比很低。因此,提出了一种基于匹配追踪算法的信号重构方法,用于提取低信噪比的拉曼信号。该方法首先通过阈值循环迭代的方法在平均谱上找出特征峰的位置、估计峰的区间。根据峰的位置区间等信息,用高斯密度函数生成字典。在噪声谱上,根据特征峰位置和区间,将其区分为有信号区间和无信号区间,在有信号区间上利用匹配追踪算法重构被噪声所掩盖的拉曼信号。该算法不仅能够很好的逼近掩盖在噪声中的拉曼信号,且在重构信号的过程中也会对基线进行扣除,无须作基线校正处理。在仿真和实验中对该算法与常规算法进行了比较,结果证明,该算法在低信噪比条件下能够较好的恢复拉曼信号。该算法不同于传统光谱去噪算法,能同时对拉曼光谱进行了基线扣除以及噪声的处理,且能取得较为理想的结果,不需要使用不同的算法对基线和噪声分别处理。其次,在算法上我们创造性地将匹配追踪算法用于拉曼光谱信号的稀疏逼近求解。     

CCD近红外光谱谱图预处理方法研究

研究讨论了多通道电荷偶合器件（ＣＣＤ）检测器测量的近红外光谱谱图预处理方法及处理参数对光谱信噪比及校正模型质量的影响。对７００～１ １００ｎｍ范围内采用２０４８像素ＣＣＤ测定的近红外光谱,为获得较高的信噪比建议平滑一阶微分处理的窗口参数为９,二阶微分的窗口参数为１９。     

基于图像复原的高光谱图像前向像移补偿

为了提高高光谱图像空间维的图像分辨力,针对航空遥感器成像时由前向像移造成的图像模糊提出了像移补偿方法。分析了航空遥感器前向像移造成图像模糊的退化机制,对运动模糊图像进行了预处理;估计了点扩散函数和噪声功率,使用改进的维纳滤波算法对图像进行复原并以绝对平均误差、峰值信噪比作为评价标准进行了实验。在估计出模糊图像点扩散函数和噪声功率的情况下得到的结果显示:与传统的维纳滤波复原算法相比,改进的维纳滤波复原算法的图像绝对平均误差降低了9.31%,峰值信噪比提高了13.98%,表明提出的算法能够有效改善高光谱图像的像质。     

Automatic Analysis of Raman Spectra

In this paper the automatic analysis of Raman spectra is described. The method applied is so-called SRIP, i.e. “Standard Representation Independent Parameter” fitting, which has been given previosly and proven to be steadily converging, if the model has been chosen properly. The approach is extended here by introducing the interactive continuation of the analysis: some of peaks may be rejected or left in the model with fixed up parameters of the position and full width at half maximum.

The main improvements of the algorithm is to be applied to the Raman spectra analysis include the mixed mathematical model as well as the enhanced sensitivity in discovering of peaks. That is achieved by the analysis of smoothed residuals at the steps of the peak revelation.

This approach enables successful analysis of spectra with low signal to noise ratio, without limitation in number of the peaks. The reliability of Raman band analysis was proven using overlapped spectra of solution of noninteracting liquids: carbontetrachloride (CTC), dichloromethane (DCM) and 1,2 dichloroethane (DCE) with different molar ratio. Solution spectra can be calculated from component spectra and compared with analysis by described method.