计算扩展目标夏克-哈特曼波前传感器子图像偏移量的相关函数质心法研究

扩展目标夏克-哈特曼波前传感器子图像之间偏移量的计算是影响波前传感精度的关键,通常采用相关算法来实现,并通过抛物线插值等方法来达到亚像元精度。子图像相对偏移量的计算也可以采用计算相关函数质心的方法来实现,其主要步骤是先计算子图像间的相关函数,在此基础上计算相关函数的质心,达到亚像元精度。通过仿真研究表明这种算法的精度与进行相关运算时的图像大小、计算质心时的相关函数窗口大小以及相关函数阈值的设定有关;同时,图像的信噪比也会影响算法的精度。研究表明,图像的信噪比小于1时,质心算法的计算误差相对较大;当图像的信噪比高于2时,相关函数质心算法的误差大约是抛物线插值法误差的一半。实验结果与仿真结果也基本吻合。     

基于峰值信噪比和小波方向特性的图像奇异值去噪技术

 提出一种利用小波变换子图像不同的方向特性和峰值信噪比进行奇异值分解的图像去噪算法。由于图像经过小波变换后,低频子图像集中了原图像的大部分能量噪声,故仅作简单维纳滤波;而噪声则主要集中在小波域中的三个不同方向的高频子图中,且系数较小,因此可以利用奇异值分解进行去噪处理,即用较大的奇异值和对应的特征向量重构出去噪图像,然而由于奇异值分解固有的行列方向性,对于高频对角线子图重构出的图像去噪效果不理想,故采取旋转至行列方向后再进行常用的奇异值滤波;最后将去噪后的低频和高频子图进行小波反变换重构出最终的去噪图像,其中重构所需的奇异值个数由图像的峰值信噪比确定。 实验结果表明,该方法在有效去噪的同时较好的保留了原有的高频细节信息。     

改进的傅里叶域小波域联合去模糊算法

傅里叶域与小波域的联合去模糊算法在低噪声时具有优越的恢复效果,但是这种联合去模糊算法并不适用于含噪声的模糊图像.为了解决这一问题,本文将先验约束分别引入傅里叶域的去模糊步骤和小波域的去噪步骤.在傅里叶域,用矩阵形式表示目标函数.对目标函数添加平滑约束并且通过噪声水平和模糊图像高频信息计算得到平滑约束项的滤波系数.同样方式,在小波域对小波域目标函数添加能量约束,实现小波域目标函数的正则化过程.分析傅里叶域的噪声放大程度,通过傅里叶域的滤波系数计算得到小波域能量约束的滤波系数.傅里叶域的平滑约束可以抑制滤波过程中噪声的产生,小波域的能量约束可以提高小波域滤波的鲁棒性.仿真实验表明,改进的算法相比于原始算法具有更好的鲁棒性,可以有效提高图像的恢复质量.对于噪声标准差为0.010.1的模糊图像,改进算法恢复图像峰值信噪比比原始算法恢复图像的峰值信噪比高1左右.并且改进算法对于高斯型点扩散函数误差具有鲁棒性,当点扩散函数估计方差与实际方差相差0.4时,改进算法的恢复效果仍优于原始算法.     

小波双线性插值迭代算法应用于光学遥感图像

分析了小波双线性插值中高频外推阈值门限与重建图像峰值信噪比的变化关系，提出了峰值信噪比最大小波双线性插值迭代算法.提出的算法能够自动搜索到峰值信噪比最大的高频外推最佳阈值门限，实现了在不破坏光学遥感图像原始信息的情况下，提高图像的空间分辨率，有利于对图像的细节信息进行观察分析.实验结果表明，该算法重建图像的峰值信噪比比双线性插值和全小波插值重建图像的峰值信噪比高5.5 dB和2.5 dB，重建图像的熵增加到原图像的1.3倍.     

小波双线性插值搜索算法及其在光学遥感图像中的应用

详细分析了在小波双线性插值中高频外推阈值门限与峰值信噪比的变化关系,提出了基于峰值信噪比最大的小波双线性插值搜索算法。提出的算法能够自动搜索到峰值信噪比最大的高频外推最佳阈值门限,实现了在不破坏光学遥感图像原始信息的情况下,提高了图像的空间分辨率,有利于对图像的细节信息进行观察分析。实验结果表明:该算法能够得到比双线性插值和全小波插值更高的峰值信噪比、熵值和更好的图像细节效果,是一种适合提高光学遥感图像分辨率的有效算法。     

基于小波分解的医学显微图像融合

提出了基于小波分解的医学显微图像融合。通过先将图像进行小波分解,并对小波分解后的不同频率域分别进行了讨论,即分别讨论了选择高频系数和低频系数的原则。选择低频系数时,设计了两种选择方案,即区域能量法和边缘选择法。选择高频系数时,设计了两种选择方案,即区域能量法和目标清晰与模糊判据法。最后选择了在低频系数时采用边缘选择法,在高频系数时采用目标清晰与模糊判据法。从仿真结果的比较来看,在将多个目标聚焦图像融合后,图像能很好地保留多幅原来图像清晰部分的信息,融合后,提高了整幅图像的信噪比,从而获得了整幅高清晰图像。     

亚像元几何图像成像与超分辨恢复算法

随着光学成像到光电数字成像的转变,如何提高CCD的几何分辨率已成为研制高分辨光电成像系统亟待解决的问题。从研究现状入手,给出了现有算法并指出不足之处`,建立了亚像元超分辨成像数学模型,提出了亚像元的CCD几何超分辨方法:将两片线阵CCD集成在同一器件中,在线阵方向上错开半个像元,同时读出时间减半,最终交织重组图像数据,合成高分辨率图像。利用MATLAB软件对双线性插值方法及亚像元成像方法进行了仿真,并定性定量地分析了两种方法的效果。结果表明:亚像元方法合成图像分辨率约为低分辨率图像的2倍,且两组仿真图像中的峰值信噪比比双线性插值图像分别高出1.4864dB和2.2070dB,该方法可以显著地减轻欠采样引起的图像模糊,且实时性优于双线性插值方法。     

一种TDI CCD亚像元图像合成方法

通过分析TDI CCD亚像元相机输出数据的空间和频谱特点,设计了亚像元插值算法,由相机输出的两幅原始图像经过插值融合处理得到一幅比原图像分辨率高的图像.仿真结果表明,该算法较其它算法得到的高分辨率图像的效果更佳,融合之后的图像比原图像分辨率提高至少1.4倍.     

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。     

泵浦激光器驰豫振荡噪声对光纤激光水听器的影响

对采用相位生成载波解调的光纤激光水听器系统中3kHz附近频域内固有噪声的产生机理进行了理论推导,并设计实验进行验证.首先测量得到泵浦激光器的驰豫振荡频率峰值,随后以400 Hz为间隔逐渐降低相位生成载波信号频率,观察固有噪声峰值的移动方向和大小.实验结果表明,随着载波信号频率的降低,固有噪声峰也向低频方向移动,移动间隔同样为400 Hz.可知相位生成载波解调算法中高频载波调制信号与泵浦激光器的驰豫振荡频率叠加是形成探测频谱固有噪声的主要原因.通过降低高频载波调制信号频率的方法对驰豫振荡噪声进行抑制,消除了探测频谱中的固有噪声峰,得到了较为平坦的本底噪声谱.     

Method of improved scatterer size estimation and application to parametric imaging using ultrasound

The frequency dependence of RF signals backscattered from random media (tissues) has been used to describe the microstructure of the media. The frequency dependence of the backscattered RF signal is seen in the power spectrum. Estimates of scatterer properties (average scatterer size) from an interrogated medium are made by minimizing the average squared deviation (MASD) between the measured power spectrum and a theoretical power spectrum over an analysis bandwidth. Estimates of the scatterer properties become increasingly inaccurate as the average signal to noise ratio (SNR) over the analysis bandwidth becomes smaller. Some frequency components in the analysis bandwidth of the measured power spectrum will have smaller SNR than other frequency components. The accuracy of estimates can be improved by weighting the frequency components that have the smallest SNR less than the frequencies with the largest SNR in the MASD. A weighting function is devised that minimizes the noise effects on the estimates of the average scatterer sizes. Simulations and phantom experiments are conducted that show the weighting function gives improved estimates in an attenuating medium. The weighting function is applied to parametric images using scatterer size estimates of a rat that had developed a spontaneous mammary tumor.     

梯度算子选择对基于梯度的亚像素位移算法的影响

基于梯度的亚像素位移算法中不同的灰度梯度计算方法对计算结果的影响进行了研究,列出了几种常用灰度梯度计算方法,并用对相邻5像素点的离散灰度进行三次样条插值的方法推导出两种灰度梯度算子。然后对计算机模拟生成的散斑图像对用各种梯度算子计算得出的亚像素位移与预先设定的真实值做了比较,给出了相应的均值误差和均值相对误差。最后的真实试件的刚体平移和单向拉伸实验结果表明,Barron算子是所列的几种梯度算法中最为精确、稳定的梯度算子。     

基于LCEEMD的低信噪比拉曼光谱自适应去噪方法研究

在生物体拉曼光谱快速采集或低功率采集过程中，往往会获得低信噪比拉曼光谱。针对低信噪比光谱数据，提出应用补充总体经验模态方法(CEEMD)分解拉曼光谱，并且依据特征模态分量的归一化排列熵值(NPE)按比例扣除噪声成分的方法，称为局部补充总体均值经验模分解方法(LCEEMD)。LCEEMD方法不仅解决了经验模态(EMD)分解中高频信号与噪声的模态混叠问题，还有效降低了总体经验模态分解法(EEMD)中的残留噪声。仿真数据实验显示，LCEEMD方法在处理10db信噪比模拟光谱时获得了39.615 0 db信噪比，0.001 17标准差和0.999 9相关系数。在人体皮肤拉曼光谱试验中，LCEEMD方法滤波后数据准确呈现出角质层脂质酰胺I带激发拉曼强谱峰以及甘油三酸酯中(CO)酯微弱谱峰。在水稻叶片可溶性糖定量预测模型中，LCEEMD方法取得了0.871 7预测相关系数和0.912 0预测标准误差，优于EMD和EEMD软阈值去噪(0.511 4，1.647 8和0.638 2，1.508 8)。LCEEMD方法实施过程中，根据去噪性能指标反馈调整归一化排列熵阈值，直至获得最佳去噪效果，滤波过程无需参数设置，可以自适应实现。     

卷积稀疏表示图像融合与超分辨率联合实现

为避免图像融合与超分辨率分步实现的不足,提出了基于卷积稀疏表示的融合与超分辨率重建联合实现方法。假设低分辨率与高分辨率图像之间具有相同的稀疏特征图,设计了一种高、低分辨率滤波器联合学习框架,实现对图像高低频成分的分离,并根据不同成分的形态特性设计了不同的融合规则:对于高频成分,根据稀疏特征图亮度信息和像素活跃性水平,设计了一种像素显著性度量方案来指导高频特征图的融合;对于低频成分,根据脉冲耦合神经网络能捕获邻域相似像素点火的特性,设计了低频成分融合方法。所提方法不需要将图像分割成重叠的块,避免块向量化的缺陷。实验结果表明,能有效提高图像融合的质量。     

Image pre-filtering for measurement error reduction in digital image correlation

In digital image correlation, the sub-pixel intensity interpolation causes a systematic error in the measured displacements. The error increases toward high-frequency component of the speckle pattern. In practice, a captured image is usually corrupted by additive white noise. The noise introduces additional energy in the high frequencies and therefore raises the systematic error. Meanwhile, the noise also elevates the random error which increases with the noise power. In order to reduce the systematic error and the random error of the measurements, we apply a pre-filtering to the images prior to the correlation so that the high-frequency contents are suppressed. Two spatial-domain filters (binomial and Gaussian) and two frequency-domain filters (Butterworth and Wiener) are tested on speckle images undergoing both simulated and real-world translations. By evaluating the errors of the various combinations of speckle patterns, interpolators, noise levels, and filter configurations, we come to the following conclusions. All the four filters are able to reduce the systematic error. Meanwhile, the random error can also be reduced if the signal power is mainly distributed around DC. For high-frequency speckle patterns, the low-pass filters (binomial, Gaussian and Butterworth) slightly increase the random error and Butterworth filter produces the lowest random error among them. By using Wiener filter with over-estimated noise power, the random error can be reduced but the resultant systematic error is higher than that of low-pass filters. In general, Butterworth filter is recommended for error reduction due to its flexibility of passband selection and maximal preservation of the allowed frequencies. Binomial filter enables efficient implementation and thus becomes a good option if computational cost is a critical issue. While used together with pre-filtering, B-spline interpolator produces lower systematic error than bicubic interpolator and similar level of the random error. Cubic B-spline interpolator can achieve comparable efficiency as bicubic interpolator, while quintic B-spline interpolator requires about 1.5 times the running time.     

Accurate definition of correlation peak position by optical speckle-displacement correlation technique

An optical speckle-displacement correlator based on hybrid optical–digital joint transform correlator architecture with a digital first stage and an optical second stage has been used to determine the correlation peak position with subpixel accuracy, without the use of intricate interpolation algorithms. A thorough analysis and a calculation of the parameters of the second optical stage are performed in order to achieve the necessary magnification of the correlation peak, so as to obtain an accurate definition of the peak position. The experiment setup for the realization of the optical speckle-displacement technique was constructed with a digital Fourier processor as its basic component, making possible a joint power spectrum median and ring median binarization, and an optical Fourier processor. The results which were obtained demonstrate that a setup of this kind can produce sharp and narrow correlation peaks, and can provide the necessary magnification for finding the peak position with subpixel accuracy.     

A subpixel motion estimation algorithm based on digital correlation for illumination variant and noise image sequences

One of the challenges in practical subpixel motion estimation is how to obtain high accuracy with sufficient robustness to both illumination variations and additive noise. Motivated by the fact that the normalized spatial cross-correlation is invariant to illumination, we introduce a gradient-based subpixel registration method by maximizing the digital correlation (DC) function between the reference and target frames. Such DC function is remodeled with the presence of image noise, yielding that the correlation coefficient is only sensitive to noise standard variance. To fairly suppress the noise corruption, not only the target frame but also the reference one is reformulated into Taylor gradient expression with half but opposite motion vector. The final solution to motion estimates can be approximated into a closed form by reserving first-order coefficient terms of unregistered motion variables. The error trend of approximated solution is discussed. Computer simulations and actual experiments’ results demonstrate the superiority of the proposed method to the LMSE-based method and ordinary DC method when illumination variations and noise exist. Among the experiments, the influences of real subpixel translation value and noise variance degree on accuracy are studied; correspondingly, an optimized iterative idea for big translations and the recommended noise level adaptive to our method are introduced.     

Accuracy enhancement of digital image correlation with B-spline interpolation

The interpolation algorithm plays an essential role in the digital image correlation (DIC) technique for shape, deformation, and motion measurements with subpixel accuracies. At the present, little effort has been made to improve the interpolation methods used in DIC. In this Letter, a family of recursive interpolation schemes based on B-spline representation and its inverse gradient weighting version is employed to enhance the accuracy of DIC analysis. Theories are introduced, and simulation results are presented to illustrate the effectiveness of the method as compared with the common bicubic interpolation.     

基于极值统计的拉曼光谱信噪比评估方法与应用

随着近年来便携式光谱仪技术的迅速发展，CCD光谱仪相对于传统光谱仪在光谱收集方式上发生了很多变化：（1）采集到的光谱对信号进行叠加积分，传统信噪比评估方法无法通过单次检测获得探测器波动；（2）对于谱图噪声（谱线随机波动），由探测器响应随机波动和扫描重复误差转变为CCD探测器像素响应差异、探测器随机噪声和与光学系统分辨力有关的模式噪声。噪声类型发生改变，导致原有的光谱质量评价方法适用性变差，基于实测光谱提出更具适应性的光谱质量评价方法具有很强的现实意义。根据拉曼光谱仪检测器的变化，对采集光谱信号的成分进行分析，在该分析的基础上提出了CCD光谱仪的噪声模型假设，根据该假设使用不同的信号极值点频率对不同的噪声进行像素分离，并对噪声频率模式进行了数值模拟，模拟结果与假设相符；在此基础上提出并实验验证了通过谱线极值间距评估谱线噪声的拉曼光谱信噪比评估方法，该方法包括以下两个步骤：（1）通过采集多次实测光谱进行叠加，叠加过程中对对应不同频次的光谱极值点数量进行统计，得到统计结果后基于文中规律分离光谱仪中的环境噪声和暗噪声；（2）应用上述分离结果，对实测光谱中对应暗噪声的谱线极值点作统计平均，再将该值应用于文中公式，计算得到信噪比。该方法在进行了步骤（1）的前期准备后，可以通过单张谱图评估CCD拉曼光谱仪的随机噪声，并用于评估光谱的信噪比。基于光学构架相同、CCD探测器不同的三个拉曼光谱系统进行实验，采用该方法通过设定信噪比阈值对谱图质量进行控制，获得了一致的光谱曲线；基于该方法对同步叠加平均法进行信噪比拟合，拟合优度达到98%。该方法可用于拉曼光谱仪的性能评估和获取拉曼光谱谱图的质量实时控制。理论和实验表明：对于基于CCD探测器的拉曼光谱仪器，当确定样品和特征峰时，可以基于此方法获得信噪比。该方法还可用于比对不同配置的拉曼光谱设备，以及作为控制谱图质量一致性的标准，并对基于拉曼光谱技术的智能鉴别系统的开发具有指导意义。     

Stochastic resonance of bias signal-modulated noise in a single-mode laser＊

Stochastic resonance (SR) for bias signal modulation is studied in a single-mode laser system. By investigating a gain-noise model driven by correlated pump noise and quantum noise, we find that, whether the correlation coefficient between both the noises is positive or negative, SR always appears in the dependence of signal-to-noise ratio (SNR) upon the noise correlation time and the frequency of the modulation signal. However, only when the correlation coefficient between both noises is negative can SR occur in the dependence of SNR upon the quantum noise intensity and pump noise intensity, while when the correlation coefficient between both noises is positive, it shows monotonically.