扫描相机标定脉冲信号位置的确定及噪声处理

 扫描相机标定数据处理中的一个关键问题是如何准确确定脉冲信号的位置，实验数据的信噪比和脉冲信号位置的定义方法都会对标定结果的准确性产生影响。采用了取半高宽的方法来确定扫描相机标定脉冲信号的位置，在信噪比比较高 （大于100） 的情况下，该方法确定标定信号的位置可以达到亚像素水平。对于信噪比比较低 (小于10) 的实验数据，先采用快速傅里叶变换方法对其进行滤波，通过滤波可以极大地抑制噪声信号的影响，然后采用“半高宽法”确定脉冲信号的位置，最后得出可信的标定结果。当扫描相机定在0.3 ns的扫描档时，通过该方法得到的扫描速度为0.214 ps/pixel,扫描不确定度为0.002 9 ps/pixel,拟合线性相关系数为0.999 7。     

A wavelet-based method for improving signal-to-noise ratio and contrast in MR images

Magnetic resonance (MR) images acquired with fast measurement often display poor signal-to-noise ratio (SNR) and contrast. With the advent of high temporal resolution imaging, there is a growing need to remove these noise artifacts. The noise in magnitude MR images is signal-dependent (Rician), whereas most de-noising algorithms assume additive Gaussian (white) noise. However, the Rician distribution only looks Gaussian at high SNR. Some recent work by Nowak employs a wavelet-based method for de-noising the square magnitude images, and explicitly takes into account the Rician nature of the noise distribution. In this article, we apply a wavelet de-noising algorithm directly to the complex image obtained as the Fourier transform of the raw k-space two-channel (real and imaginary) data. By retaining the complex image, we are able to de-noise not only magnitude images but also phase images. A multiscale (complex) wavelet-domain Wiener-type filter is derived. The algorithm preserves edges better when the Haar wavelet rather than smoother wavelets, such as those of Daubechies, are used. The algorithm was tested on a simulated image to which various levels of noise were added, on several EPI image sequences, each of different SNR, and on a pair of low SNR MR micro-images acquired using gradient echo and spin echo sequences. For the simulated data, the original image could be well recovered even for high values of noise (SNR approximately 0 dB), suggesting that the present algorithm may provide better recovery of the contrast than Nowak's method. The mean-square error, bias, and variance are computed for the simulated images. Over a range of amounts of added noise, the present method is shown to give smaller bias than when using a soft threshold, and smaller variance than a hard threshold; in general, it provides a better bias-variance balance than either hard or soft threshold methods. For the EPI (MR) images, contrast improvements of up to 8% (for SNR = 33 dB) were found. In general, the improvement in contrast was greater the lower the original SNR, for example, up to 50% contrast improvement for SNR of about 20 dB in micro-imaging. Applications of the algorithm to the segmentation of medical images, to micro-imaging and angiography (where the correct preservation of phase is important for flow encoding to be possible), as well as to de-noising time series of functional MR images, are discussed.     

Signal-to-noise ratio evaluation of a CCD camera

A fast signal-to-noise ratio (SNR) digital test method for a CCD camera is presented in this study. The proposed method employs the conventionally used differential operations of two sequential images to determine the noise. However, the technique focuses on two features to improve the SNR evaluation: the noise is separated from the differential image by a specially designed digital high-pass filter that does not affect the noise intensity; and the additional quantization noise introduced into the digital image by the frame grabber is corrected for in the final calculation. The method can produce an objective measurement that offers high repeatability. The results obtained are consistent with those produced by industry standard instruments.     

Time-domain noise reduction based on an orthogonal decomposition for desired signal extraction

This paper addresses the problem of noise reduction in the time domain where the clean speech sample at every time instant is estimated by filtering a vector of the noisy speech signal. Such a clean speech estimate consists of both the filtered speech and residual noise (filtered noise) as the noisy vector is the sum of the clean speech and noise vectors. Traditionally, the filtered speech is treated as the desired signal after noise reduction. This paper proposes to decompose the clean speech vector into two orthogonal components: one is correlated and the other is uncorrelated with the current clean speech sample. While the correlated component helps estimate the clean speech, it is shown that the uncorrelated component interferes with the estimation, just as the additive noise. Based on this orthogonal decomposition, the paper presents a way to define the error signal and cost functions and addresses the issue of how to design different optimal noise reduction filters by optimizing these cost functions. Specifically, it discusses how to design the maximum SNR filter, the Wiener filter, the minimum variance distortionless response (MVDR) filter, the tradeoff filter, and the linearly constrained minimum variance (LCMV) filter. It demonstrates that the maximum SNR, Wiener, MVDR, and tradeoff filters are identical up to a scaling factor. It also shows from the orthogonal decomposition that many performance measures can be defined, which seem to be more appropriate than the traditional ones for the evaluation of the noise reduction filters.     

CCD摄像机的输出调制度阈值分析

应用数理统计学的有关内容对CCD输出信号中的随机噪声进行了相关分析。引入了“噪声等效调制度”这一概念 ,利用计算机模拟技术对摄像机成像时所产生的随机噪声进行了模拟与计算。通过计算机模拟 ,推导出了噪声等效调制度与CCD摄像机系统信噪比之间的关系。将信噪比对CCD摄像机成像质量的影响予以量化 ,并对摄像机的输出调制度阈值进行了分析与计算     

三波段微光彩色夜视方法研究

为克服夜视设备产生单色图像的缺陷,得到更符合人眼视觉的彩色夜视图像。根据RGB理论模型以及滤光片的分谱作用原理,基于第二代像增强器设计出一种彩色夜视方案,通过测量滤光片的光谱透过率,得出滤光片对像增强器信噪比的影响;提出利用全波图像的四帧融合解决像增强器信噪比低的问题,并进行实验验证。实验结果显示室内和室外情况下四帧融合彩色图像熵和方差分别达到6.8、35.39及7.0、45.07,均优于三帧融合时对应值,说明提出的四帧融合方法能够克服信噪比降低的缺陷,得到清晰且信息量丰富的夜视图像。     

The effects of SNR on ADC measurements in diffusion-weighted hyperpolarized He-3 MRI

The theoretical dependence of the mean and standard deviation of ADC values on signal-to-noise ratio (SNR) was derived and compared to measured values in porous phantoms and the lungs of human subjects using diffusion-weighted hyperpolarized helium-3 MRI. For SNR values below 15, mean ADC values were highly SNR-dependent due to a combination of noise and choice of noise thresholding. Above SNR values of 15 and for mean ADC values within ranges relevant for evaluating lung disease (<0.6 cm2/s), the mean ADC was largely independent of SNR. The standard deviation, by contrast, was highly dependent on SNR over a much larger range, but this dependence was well predicted by theory, suggesting the histogram of ADC values might be corrected for these stochastic processes to more accurately evaluate disease using restricted diffusion measures in the lungs.     

基于自适应随机共振理论的太赫兹雷达信号检测方法

太赫兹雷达系统在差频信号频谱分析过程中,干扰噪声影响其测距能力.针对上述问题,提出基于自适应随机共振理论的太赫兹雷达信号检测方法,通过对含噪差频信号进行二次采样,利用自适应随机共振系统提取信号,进行尺度恢复完成测距计算.实验数据显示,不同测量距离时,相较于快速傅里叶变换法,输出信噪比的平均增益为9.684 d B,其中测量距离为1000 mm处,差频信号初始频谱值提高了64.1倍,系统信噪比增益为11.761 d B;相较于滤波法,在测量距离为1000 mm处信噪比增益最大,提高了70.56%;输入噪声强度为1—5 V之间时,输出信噪比曲线的曲率相对于滤波法降低了86.5%,其中噪声强度为5 V时信噪比增益最大,为14.018 d B.实验表明太赫兹雷达系统的测距能力大幅提高.     

高光谱遥感图像微分域三维混合去噪方法

高光谱遥感图像是一种三维数据,由二维空间信息和一维光谱信息组成。普通的对二维静态图像或一维光谱信息去噪的算法忽视了高光谱图像强烈的谱间相关性和图谱合一的特点,无法取得令人满意的效果。同时现代的高光谱遥感图像噪声级别相对较低,噪声方差随波段不同而不同。针对以上特点,提出一种微分域三维混合去噪方法。首先将高光谱遥感图像变换到光谱微分域,使细微的噪声变得显著。然后在微分域中,对二维空间域采用基于小波的非线性阈值去噪BayesShrink算法。为克服噪声方差不同的特点,对光谱维不再采用小波阈值去噪方法,而采用Savitzky-Golay滤波进行平滑。最后对微分域去噪平滑处理后的图像进行光谱积分,并进行积分修正,消除光谱积分中引入的积累误差。对信噪比为600∶1的机载可见红外成像光谱仪数据(AVIRIS)实验表明,该算法能有效地降低噪声,将信噪比提高到2 000∶1以上。     

基于多光谱遥感成像链模型的系统信噪比分析

信噪比(SNR)是评价多光谱遥感成像性能的重要指标,在设计多光谱遥感成像仪的最初阶段应进行分析,从而确定各分系统相关参数。多光谱遥感系统的成像链模型综合考虑辐射源、地物光谱反射、大气辐射传输、光学系统成像、分光元件特性、探测器光谱响应和相机噪声等各个环节,可用于进行成像过程端对端的完整分析。以基于滤光片阵列的多光谱遥感系统为例,采用MODTRAN软件进行大气辐射传输计算,对不同太阳天顶角下,不同目标地物计算像面的照度,根据电荷耦合器件探测器的噪声模型,计算出不同工作条件下多光谱遥感系统的SNR。通过对SNR的分析,可给出该类型多光谱遥感系统获得最佳性能的工作条件,并能够结合使用要求进行光学系统参数的优化选择。     

SNR and functional sensitivity of BOLD and perfusion-based fMRI using arterial spin labeling with spiral SENSE at 3 T

Blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) studies using parallel imaging to reduce the readout window have reported a loss in temporal signal-to-noise ratio (SNR) that is less than would be expected given a purely thermal noise model. In this study, the impact of parallel imaging on the noise components and functional sensitivity of both BOLD and perfusion-based fMRI data was investigated. Dual-echo arterial spin labeling data were acquired on five subjects using sensitivity encoding (SENSE), at reduction factors (R) of 1, 2 and 3. Direct recording of cardiac and respiratory activity during data acquisition enabled the retrospective removal of physiological noise. The temporal SNR of the perfusion time series closely followed the thermal noise prediction of a √R loss in SNR as the readout window was shortened, with temporal SNR values (relative to the R=1 data) of 0.72 and 0.56 for the R=2 and R=3 data, respectively, after accounting for physiological noise. However, the BOLD temporal SNR decreased more slowly than predicted even after accounting for physiological noise, with relative temporal SNR values of 0.80 and 0.63 for the R=2 and R=3 data, respectively. Spectral analysis revealed that the BOLD trends were dominated by low-frequency fluctuations, which were not dominant in the perfusion data due to signal processing differences. The functional sensitivity, assessed using mean F values over activated regions of interest (ROIs), followed the temporal SNR trends for the BOLD data. However, results for the perfusion data were more dependent on the threshold used for ROI selection, most likely due to the inherently low SNR of functional perfusion data.     

Wavelet Filter and Noise Rejection for the Pulse Laser Radar

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大视场空间相机轻型遮光罩的研制

空间相机遮光罩既能遮挡杂光进入相机镜头,又可利用遮光罩长度和遮光罩内的光栅及表面材料特性,吸收已进入遮光罩的杂散光,能够保证相机获得较高的信噪比。具有优良性能指标的碳纤维复合材料应用于空间相机中能够满足空间相机的结构设计指标,并能大大降低相机的重量。针对某空间相机进行了遮光罩的设计,通过利用有限元模拟仿真分析与试验验证相结合的方法,验证了碳纤维作为遮光罩材料的可行性和是否能够提高光学系统的信噪比。结果表明,碳纤维复合材料应用于空间相机遮光罩的设计是完全可行的。     

一种改进的图像组合滤波方法

利用小波阈值去噪和Wiener滤波的特点,在文献［7］的基础上提出了一种改进的组合滤波方法,在进行空域自适应滤波之前,先对经BayesShrink处理过的预去噪图像重新估计其噪声方差,通过数值计算给出了该噪声方差的一种近似最优估计公式.实验结果表明该方法在去噪图像的均方误差和对不同图像的适应性方面都得到了改善.     

改进维纳滤波器及其在目标方位估计中的应用

针对复杂的水声环境以及信噪比较低的目标信号导致方位估计性能较差的问题,本文提出了一种基于改进维纳滤波器和波束形成器的方位估计方法,该方法能够抑制噪声,提高目标方位估计性能。首先利用改进维纳滤波器抑制各通道接收数据中的噪声,提高输出信噪比。在此基础上,将改进维纳滤波器的输出通过波束形成器,获得目标的方位估计。改进维纳滤波器能够通过调整滤波器参数,控制滤波器的噪声抑制能力和信号失真。因此,针对不同的波束形成器对信号失真的敏感程度不同,可以通过调节改进维纳滤波器的参数,获得噪声抑制与信号失真之间的最佳折中,从而提高输出信噪比,降低目标方位估计的信噪比门限和均方根误差。仿真和实验结果验证了本文方法。      

空间探测相机的能量计算

建立了空间可见光相机对空探测的物理模型.利用辐射传输的基本原理,分析了面源目标亮度和背景辐射亮度与探测相角、背景光入射角和相机数值孔径之间的关系.给出点目标探测时主要噪音源的计算方法,从而推导出可见光相机接收到的以电子数为基本单位的信噪比表达式.通过数值模拟给出各种因素对信噪比的影响,得到了较高信噪比的可行方法.     

Interaural correlation sensitivity

Sensitivity to differences in interaural correlation was measured for 1.3-ERB-wide bands of noise using a 2IFC task at six frequencies: 250, 500, 750, 1000, 1250, and 1500 Hz. The sensitivity index, d', was measured for discriminations between a number of fixed pairs of correlation values. Cumulative d' functions were derived for each frequency and condition. The d' for discriminating any two values of correlation may be recovered from the cumulative d' function by the difference between cumulative d's for these values. Two conditions were employed: the noisebands were either presented in isolation (narrow-band condition) or in the context of broad, contiguous flanking bands of correlated noise (fringed condition). The cumulative d' functions showed greater sensitivity to differences in correlation close to 1 than close to 0 at low frequencies, but this difference was less pronounced in the fringed condition. Also, a more linear relationship was observed when cumulative d' was plotted as a function of the equivalent signal-to-noise ratio (SNR) in dB for each correlation value, rather than directly against correlation. The equivalent SNR was the SNR at which the interaural correlation in an NoS(pi) stimulus would equal the interaural correlation of the noise used in the experiment. The maximum cumulative d' declined above 750 Hz. This decline was steeper for the fringed than for the narrow-band condition. For the narrow-band condition, the total cumulative d' was variable across listeners. All cumulative d' functions were closely fitted using a simple two-parameter function. The complete data sets, averaged across listeners, from the fringed and narrow-band conditions were fitted using functions to describe the changes in these parameters over frequency, in order to produce an interpolated family of curves that describe sensitivity at frequencies between those tested. These curves predict the spectra recovered by the binaural system when complex sounds, such as speech, are masked by noise.     

Time-Domain Quantification of Multiple-Quantum-Filtered Na Signal Using Continuous Wavelet Transform Analysis

The application of continuous wavelet transform (CWT) analysis technique is presented to analyze multiple-quantum-filtered (MQF) ²³Na magnetic resonance spectroscopy (MRS) data. CWT acts on the free-induction-decay (FID) signal as a time-frequency variable filter. The signal-to-noise ratio (SNR) and frequency resolution of the output filter are locally increased. As a result, MQF equilibrium longitudinal magnetization and the apparent fast and slow transverse relaxation times are accurately estimated. A developed iterative algorithm based on frequency signal detection and components extraction, already proposed, was used to estimate the values of the signal parameters by analyzing simulated time-domain MQF signals and data from an agarose gel. The results obtained were compared to those obtained by measurement of signal height in frequency domain as a function of MQF preparation time and those obtained by a simple time-domain curve fitting. The comparison indicates that the CWT approach provides better results than the other tested methods that are generally used for MQF ²³Na MRS data analysis, especially when the SNR is low. The mean error on the estimated values of the amplitude signal and the apparent fast and slow transverse relaxation times for the simulated data were 2.19, 6.63, and 16.17% for CWT, signal height in frequency domain, and time-domain curve fitting methods, respectively. Another major advantage of the proposed technique is that it allows quantification of MQF ²³Na signal from a single FID and, thus, reduces the experiment time dramatically.     

基于改进中值滤波和提升小波变换的阈值去噪方法研究

对于实际拍摄的一些图像信噪比低,噪声密度大,且含有混合噪声,而现有算法大多只能去除单一噪声的问题。针对混合噪声中含有的脉冲噪声和高斯噪声,提出基于改进中值滤波和提升小波变换去噪相结合的方法。去噪过程中,使用中值滤波器提取脉冲噪声并采用中值滤波算法滤波后,构造提升小波,采用改进阈值函数提升小波阈值去噪方法去除高斯噪声。实验结果表明,当噪声值(,)=(0.4, 20)时,采用本文去噪方法,峰值信噪比（PSNR）为34.002 1,平均绝对误差（MAE）为2.365 3。     

基于四波段图像融合的彩色夜视方法研究

为了在低照度条件下获取目标的彩色图像,提高夜间对目标的识别能力,提出了基于四波段图像融合的彩色夜视方法.采用F-P滤光片设计出了透射中心在三基色光中心波长及近红外波段的四波段滤光片,在各个透射区域的平均透射率均达90%以上;将四波段滤光片设计成圆形滤色轮结构,用分光计测得了各波段滤光片的光谱透射性;对加入滤光片后的系统信噪比进行了分析和计算,分析结果表明加入滤光片不会引入噪声,计算结果表明加入蓝色、绿色、红色和近红外波段滤光片的成像系统的信噪比分别是原来单色微光夜视系统信噪比的19.59%、38.45%、47.28%和46.70%.借助国产超二代像增强器在微光实验室进行了四波段图像采集及彩色图像融合实验,实验时光照度分别为1×10~(-3)lx和1×10~(-1)lx,对获取的图像质量进行了评价.结果表明:在照度为1×10~(-3)lx时,融合的彩色图像在均值、方差和熵这三项指标上均优于过滤后的蓝色和绿色的单色图像,且由于彩色图像中利用了近红外图像进行增强,使得彩色图像亮度更高,颜色分辨性更好;在照度为1×10~(-1)lx时,融合后的彩色图像的信息熵比红、绿、蓝三种基色图像的大,彩色图像携带的信息量更大.本文的研究对彩色夜视成像系统的设计和研发具有借鉴和指导意义.