Precision of light intensity measurement in biological optical microscopy

Standardization and calibration of optical microscopy systems have become an important issue owing to the increasing role of biological imaging in high‐content screening technology. The proper interpretation of data from high‐content screening imaging experiments requires detailed information about the capabilities of the systems, including their available dynamic range, sensitivity and noise. Currently available techniques for calibration and standardization of digital microscopes commonly used in cell biology laboratories provide an estimation of stability and measurement precision (noise) of an imaging system at a single level of signal intensity. In addition, only the total noise level, not its characteristics (spectrum), is measured. We propose a novel technique for estimation of temporal variability of signal and noise in microscopic imaging. The method requires registration of a time series of images of any stationary biological specimen. The subsequent analysis involves a multi‐step process, which separates monotonic, periodic and random components of every pixel intensity change in time. The technique allows simultaneous determination of dark, photonic and multiplicative components of noise present in biological measurements. Consequently, a respective confidence interval (noise level) is obtained for each level of signal. The technique is validated using test sets of biological images with known signal and noise characteristics. The method is also applied to assess uncertainty of measurement obtained with two CCD cameras in a wide‐field microscope.     

Noise Variance Estimation Using Image Noise Cross‐Correlation Model on SEM Images

A number of techniques have been proposed during the last three decades for noise variance and signal‐to‐noise ratio (SNR) estimation in digital images. While some methods have shown reliability and accuracy in SNR and noise variance estimations, other methods are dependent on the nature of the images and perform well on a limited number of image types. In this article, we prove the accuracy and the efficiency of the image noise cross‐correlation estimation model, vs. other existing estimators, when applied to different types of scanning electron microscope images. SCANNING 35: 205‐212, 2013. © 2012 Wiley Periodicals, Inc.     

Single-image signal-to-noise ratio estimation

A method for estimating the signal-to-noise ratio from a single image is presented in this paper. The autocorrelation-based technique requires that image details be correlated over distances of a few pixels, while the noise is assumed to be uncorrelated from pixel to pixel. The latter is shown to be a good approximation in the case of scanning electron microscope (SEM) images provided that the video signal is not band limited. The noise component is derived from the difference between the image autocorrelation at zero offset and an estimate of the corresponding noise-free autocorrelation. Nonlinear effects introduced by intensity saturation and their implications on the image signal-to-noise ratio are also discussed.     

基于经典谱估计改进方法的涡街流量计

针对涡街流量计高精度、高量程比的要求,在分析涡街信号及其噪声特点的基础上,提出一种采用自适应采样频率和Welch功率谱估计相结合的涡街信号分析处理方法。该方法首先使用经典功率谱估计的FFT算法计算出信号频率的区间范围,然后将信号通过相应截止频率的低通滤波器以防止发生混叠现象,采用信号抽取的方法降低采样频率从而减小频谱的最小频率分辨率,最后采用Welch功率谱估计的方法进行谱分析提高信噪比、减少谱失真。仿真及实验结果表明:所提出的涡街信号处理方法能有效地抑制噪声,实现高精度的功率谱计算,对于提升和改进涡街流量计的性能有良好的效果。     

Performance of new signal‐to‐noise ratio estimation for SEM images based on single image noise cross‐correlation

A new technique for estimation of signal‐to‐noise ratio in scanning electron microscope images is reported. The method is based on the image noise cross‐correlation estimation model recently developed. We derive the basic performance limits on a single image signal‐to‐noise ratio estimation using the Cramer–Rao inequality. The results are compared with those from existing estimation methods including the nearest neighbourhood (the simple method), the first order linear interpolator, and the autoregressive based estimator. The comparisons were made using several tests involving different images within the performance bounds. From the results obtained, the efficiency and accuracy of image noise cross‐correlation estimation technique is considerably better than the other three methods.     

Digital beam control for fast differential voltage contrast

A new method for voltage contrast enhancement by image subtraction is presented. It is based on a modification of a commercial column automation system that digitizes beam positions and intensity signals in a scanning electron microscope (SEM). The new modulus performs via hardware all the operations of bias control and signal differentiation at each image point, resulting in a minimum acquisition time of 4 μs per point, that is less than 0.3 seconds to obtain a 256 × 256 pixels image with 8 bit gray resolution. The digital handling of intensity data, gives high precision differential images and the control of beam position prevents spatial differentiation effects, enabling noise reduction by time integration of intensity data in each point.     

Mixed lagrange time delay estimation autoregressive Wiener filter application for real-time SEM image enhancement

A new filter is developed for the enhancement of scanning electron microscope (SEM) images. A mixed Lagrange time delay estimation auto-regression (MLTDEAR)-based interpolator is used to provide an estimate of noise variance to a standard Wiener filter. A variety of images are captured and the performance of the filter is shown to surpass the conventional noise filters. As all the information required for processing is extracted from a single image, this method is not constrained by image registration requirements and thus can be applied in real-time in cases where specimen drift is presented in the SEM image.     

基于Duffing振子和ML的微弱信号幅值估计新方法

基于Du ffing振子和最大似然参量估计方法,提出一种微弱正弦信号幅值估计的新方法。介绍了新方法的原理和具体实现过程。将混有噪声的待测信号送入Du ffing系统,依据大周期工作状态下Du ffing系统具有优良的信噪比改善特性,采用最大似然法估计Du ffing系统的输出信号幅值,进一步由系统输入输出之间的关系确定输入的微弱正弦信号的幅值。通过仿真实验,对该方法和最大似然法直接用于微弱正弦信号幅值估计的结果进行了对比。实验结果表明:该方法明显提高了估计精度。     

Confocal pH imaging of microscopic specimens using fluorescence lifetimes and phase fluorometry: influence of parameter choice on system performance

We investigate the performance of confocal pH imaging when using phase fluorometry and fluorophores with pH-dependent lifetimes. In these experiments, the specimen is illuminated by a laser beam, whose intensity is sinusoidally modulated. The lifetime-dependent phase shift in the fluorescent signal is detected by a lock-in amplifier, and converted into a pH value through a calibration procedure. A theoretical investigation is made of how the different system parameters will influence the results concerning sensitivity and noise. Experiments carried out with the fluorophore SNAFL-2 support these theoretical predictions. It is found that, under realistic experimental conditions, we can expect a pH change of 0.1 units to be easily detected in an 8-bit digital image. However, the pixel-to-pixel root mean square noise is often of the order of one pH unit. This comparatively high level of noise has its origin in photon quantum noise. pH measurements on living cells show a systematic deviation from expected values. This discrepancy appears to be the result of fluorophore interaction with various cell constituents, and is the subject of further investigation.     

Collection deficiencies of scanning electron microscopy signal contrasts measured and corrected by differential hysteresis image processing

Limitations of scanning electron microscopy (SEM) image resolution and quality were measured in digital image data and their effect on image contrasts was analyzed and corrected by differential hysteresis (DH) processing. DH processing is a mathematical procedure that utilizes hysteresis properties of intensity variations in the image for a segmentation of differential contrast patterns. These patterns display contrast properties of the data as coherent full-frame images. The contrast segmentation is revertible so that the original image can be restored from the sum of the sequentially extracted DH contrast patterns. DH imaging enhances weak contrast components so that they are more easily recognizable and displays SEM image data free of signal collection efficiency contrasts. Example image data include environmental SEM (ESEM) and SEM images of low and mediumhigh magnifications where collection deficiencies included charging of the specimen surface, obstructions from specimen topography, and uneven signal collection properties of the detector. ESEM low-vacuum image data, which appear to be of high quality, contained local areas of reduced contrasts due to residual surface charging. In such areas, signal contrasts were reduced up to 80%, which suppressed most of the weak short-range contrasts. In low-magnification SEM images, up to 93% of the local high precision contrast was lost from the various adverse effects which diminished the pixel-related contrast resolution of the microscope and resulted in images with low detail. Also, at medium magnification, surface charging effects dramatically reduced the image quality because contrasts resulting from local electron beam/specimen interactions were reduced by as much as 71%. DH imaging restored the local contrast losses by elimination of the collected distorted fraction of signal contrasts and reconstitution of the collected maintained fraction. Restored DH images are of superior quality and enhance the imaging capability of the conventional SEM. DH contrast segmentation provides an improved basis for the measurement of various signal contrast components and detector performances. The DH analysis will ultimately facilitate a precise deduction of specimen properties from extracted contrast patterns.     

利用信号相关性抑制光纤陀螺强度噪声

提出了一种利用陀螺干涉信号和耦合器空闲端信号相关性估计光源强度噪声抑制效果的方法,并在现场可编程门阵列(FPGA)中进行了实时估计.根据估计结果,判决是否进行强度噪声相减,以提高光纤陀螺强度噪声抑制方法的可靠性.理论分析表明,强度噪声抑制效果与信号相关性直接相关.利用该方法,对某高精度干涉型光纤陀螺进行了实验.结果表明,当陀螺干涉信号和耦合器空闲端信号互相关系数为0.91时,干涉信号噪声方差降低至17.16％,然而,当上述互相关系数为0.28时,噪声相减法反而使干涉信号噪声方差增大至143.18％,由此验证了理论分析结果.利用该方法可以在线检测陀螺干涉信号和耦合器空闲端信号的相关性,进而避免噪声相减法中当陀螺干涉信号和耦合器空闲端信号相关性较差时,光纤陀螺噪声不降反升的情况,提高了强度噪声相减法的可靠性.     

相差式测量仪表零点误差的分析

本文在典型的相差式测量仪表基本结构的讨论基础上,分析了电路系统中两信号通道模拟单元相位特性的差异以及数字单元中转换环节等在时间动态特性上的非一致性,从而揭示这类仪表零点误差的来源,形成及特点。本文的工作为研究在线自动校正技术提供了重要的依据。     

基于传递函数估计的近场声全息的噪声源识别

在近场声全息(NAH)声场测量中,噪声的存在使近场声全息重建精度降低,影响声场重建的实现。本文提出一种基于传递函数估计的双测量面NAH技术,首先采用双测量面对噪声源信号进行测量,然后基于传递函数法引入一种合理的传递函数估计,结合参考传声器信号来求解全息面复声压,最后利用前后测量面数据相位差异来求解格林函数,根据声场重建公式进行近场声全息声场重建。数值仿真及重建误差分析表明,存在测量噪声影响的情况下,本文提出的方法相比传递函数法NAH重建误差更小,能够更准确地识别声源位置并提高声全息重建精度。最后对某型拖拉机前端进行近场阵列扫描试验,验证基于传递函数估计的双测量面NAH的有效性。     

Note: In vivo pH imaging system using luminescent indicator and color camera

Microscopic in vivo pH imaging system is developed that can capture the luminescent- and color-imaging. The former gives a quantitative measurement of a pH distribution in vivo. The latter captures the structural information that can be overlaid to the pH distribution for correlating the structure of a specimen and its pH distribution. By using a digital color camera, a luminescent image as well as a color image is obtained. The system uses HPTS (8-hydroxypyrene-1,3,6-trisulfonate) as a luminescent pH indicator for the luminescent imaging. Filter units are mounted in the microscope, which extract two luminescent images for using the excitation-ratio method. A ratio of the two images is converted to a pH distribution through a priori pH calibration. An application of the system to epidermal cells of Lactuca Sativa L is shown.     

基于自适应Kalman滤波的SAW测温数据纠错方法

在无源无线SAW测温系统实际应用中,阅读器接收到的信号往往受到其所处环境电磁波的干扰。这些干扰将会使阅读器得到错误的测量数据。温度变化趋势和测量噪声时变的特点也给系统建模以及噪声估计带来了困难。针对实际应用中存在的问题,在Kalman滤波的基础之上,提出了一种新的自适应算法。该算法采用多项式预测的方法建立温度测量的时变系统模型,根据当前及历史测量值,自行调整预测模型参数,避免因模型不准确造成Kalman滤波效果严重下降的问题;通过对测量数据小波变换的方法,实时估计测量数据噪声方差,克服未知观测噪声的条件下精度下降的问题;当测量数据受到干扰时,测量值与纠错值之间的差值不满足高斯分布,通过对差值统计特性的分析,对测量数据进行错误数据判别与剔除,有效地抑制干扰对温度测量的影响。将这种自适应Kalman滤波算法应用到无源无线SAW测温系统中,无源无线SAW温度传感器测温实验的结果验证了该算法能有效地纠正粗大误差,提高测量系统的精度。     

面向微纳材料的激光扫描二维成像系统

在对微纳材料光学特性表征中,需要获得分辨率更高的波长和强度的荧光图像。普通的显微镜无法满足测试的要求,因此将普通的成像显微镜、光谱仪以及纳米移动台组成激光扫描显微镜成像系统,并利用LabVIEW开发了一套完整的集二维扫描采集与信号图像处理一体的系统上位机软件。扫描采集过程使用了低通滤波等数字信号处理方法消除光谱仪信号噪声的影响。利用本系统测量硒化镉纳米带、单层二硫化钼得到了荧光强度图像以及荧光峰值波长图像,能分辨出最小波长为0.03 nm的荧光。将采集长度与实际长度进行比较并分析荧光强度差异,取得了较好的效果。     

小型化硅微谐振式加速度计的实现与性能测试

设计了一款由微机电系统和专用集成电路构成的小型化硅微谐振式加速度计。该加速度计采用80μm厚SOI工艺加工微机电系统(MEMS)结构,采取真空封装技术降低结构噪声。首先,采用振荡信号作为自动增益控制电路中斩波器的控制信号,降低了闪变噪声且不会引入额外的功耗。其次,使用线性区工作的乘法器取代传统的吉尔伯特单元,通过大幅降低系统总体供电电压来降低功耗。最后,采用复位计数器进行频率数字转换,在所关心的带宽内抑制量化噪声。实验显示:该加速度计在达到±30 g线性量程的前提下,实现了2.5μg/√Hz的分辨率和1μg的零偏不稳定度。此外,为了减小电路自身发热引起的温度漂移,该样机的功耗被控制在3.5mW以内,系统集成后的尺寸约为45mm×30mm×20mm。基于所述技术,系统在体积、功耗和性能方面均有较大的提升。     

A routine correction for electron beam intensity variation during quantitative EDS microanalysis using continuum radiation

A detailed investigation of the relationship between the mean atomic number and the intensity of high energy continuum radiation has verified earlier studies in defining a linear relationship. Corrections for matrix effects on the continuum intensity are found to be unnecessary within the precision limits of the data. Incorporation of this relationship into a quantitative energy-dispersive spectrometer (EDS) microanalysis program allows internal correction for electron beam intensity variations between standard and unknown specimen analysis. It therefore allows quantitative analysis without normalisation on systems lacking any form of electron beam current measurement. Within limits, the need for reproducibility of electron beam intensity and counting time is eliminated.     

Accuracy and precision of quantitative energy-dispersive x-ray spectrometry in the environmental scanning electron microscope

The accuracy and precision of quantitative energy-dispersive x-ray spectrometry in the environmental scanning electron microscope have been estimated using a series of copper / gold alloys of known composition. The mean values (five to six replicate experiments) had relative errors within +/- 5%, and most were within +/- 3.5%. All relative standard deviations were < 5% and most were < 3%. Since the standard specimens were large (approximately 500 microm) in diameter, electron scattering in the 2 torr of water vapor above the specimen did not affect the results. This level of accuracy and precision was possible only by using a novel specimen surface charge neutralization scheme.     

A new velocity estimation method using spectral identification of noise

In all measurement techniques one seeks accuracy and precision. In ultrasonic Doppler velocimetry, those qualities strongly depend on signal to noise ratio of the Doppler signal and on the performance of the velocity estimator. The most widely used estimation method in ultrasonic coherent Doppler velocimetry is the pulse pair method. Its success is due to the computation efficiency of the algorithm combined to an unbiased estimator. Unfortunately, for a wide range of experimental fluid flows, the pulse pair estimation is less efficient, especially for clear water or concentrated mud where the signal to noise ratio can be very low, or for highly turbulent flows where the Doppler signal has a broad spectrum. Our approach is based on the treatment of the Doppler spectral information. It uses a simple parametric identification inspired by theoretical models and experimental observations. It acts through noise subtraction and subsequent cutting. Thus, we have developed a fast velocity estimation algorithm superior to the pulse pair one in terms of accuracy. The robustness of the method was evaluated by adding different levels of white Gaussian noise to an experimental Doppler signal. The results demonstrate an increase of noise immunity up to one decade compared to the pulse pair method.