高阶截断误差的斜率和曲率混合型波前重构算法

研究了斜率和曲率混合型区域波前重构算法,提出了通过减小重构方程的截断误差来提高波前重构精度。利用泰勒展开推导了波前值、波前斜率和曲率值三者间的数学关系,得到了截断误差为相邻两波前测量点间距五次方的重构方程。将该方程用于波前重构中,提出了一种新的斜率和曲率混合型波前重构算法。通过重构仿真对比了该混合型算法与现有混合型算法的波前重构误差。结果表明,在忽略测量噪声的情况下,提出的算法将相对重构误差降低了约两个数量级;在考虑测量噪声的情况下,提出的算法在对高阶像差的重构时,具有更小的相对重构误差。提出的高阶截断误差的混合型波前重构算法较现有的混合型算法需要的计算量更小,更利于实时波前重构。     

基于多对流速度的波前重构算法研究

 在气动光学研究中,Ronald J. Hugo 和Eric J. Jumper的小孔径光束技术(SABT)波前重构算法在理论推导中忽略了与涡结构尺度相关的对流速度的差异,因此必然会给波前重构带来误差。用小波分析提取了上、下游探测光束输出的不同尺度的光程信号,通过计算两个探测光束输出的同一尺度信号的互相关系数,并利用互相关系数达到最大值对应的延迟时间研究了尺度相关的对流速度,然后再进行尺度相关的小孔径光束波前重构。结果表明：相对于单一对流速度的小孔径光束波前重构算法,该尺度相关的波前重构算法能有效地提高波前重构的精度。     

中心不重合径向剪切干涉迭代波前重构算法仿真分析

径向剪切干涉测量时经常会出现扩束与缩束光波中心不重合情况,传统波前重构算法会导致较大重构误差,其应用受到挑战。推导了中心不重合径向剪切干涉迭代波前重构算法,仿真分析了组合像差、单阶Zernike像差、中心偏移量大小及其计算误差对重构算法的影响。结果表明,在剪切光波中心不重合情况下,该文算法能够准确进行波前重构,重构效果显著优于传统算法;在论文仿真条件下,随着中心偏移量的增大,本文算法重构波面均方根误差（RMS）不高于0.05λ,而传统算法重构误差RMS值达1.6λ且与偏移量近似线性相关。     

一种基于离散数据从局部到全局的网络重构算法

网络的结构和功能彼此相互影响,网络上的功能往往体现为网络上的动力学过程,网络上的动力学过程通过网络中的行为表象数据进行体现.因此,根据网络上可观测的相关数据对网络结构进行重构将成为可能.本文拟解决如何根据网络上可观测的离散数据还原网络拓扑结构的问题,提出了在网络局部利用每一条离散数据对应节点的相似程度来推测节点间发生连边的可能性,通过多条离散数据重构网络各个局部拓扑并将由多条数据得到的局部拓扑进行叠加,最终重构出整个网络的全局拓扑结构的算法.为了验证算法的可行性与准确性,在小世界、无标度和随机网络中进行了网络重构实验,通过在三种不同类型及不同规模的网络中进行网络重构实验可以看出,网络重构算法在不同类型网络中的表现也不同,且网络的平均度值也会影响网络重构算法对数据的要求.为了验证算法的适用性,对三个实际网络进行了网络重构实验,结果显示算法能够适用实际较大规模网络的重构.该算法具有很好的适用性和准确度,适合不同类型网络的拓扑结构重构场景.     

星间光通信系统中多样化波前畸变的小波重构

用小波变换方法对星间光通信中的多样化波前畸变进行重构,并分析了小波重构方法的两项参考指标:重构精度和重构算法复杂度。基于对这两项指标的综合考虑,提出一种最优小波基函数的选取方法。仿真数据表明,利用最优小波基函数选取方法对波前畸变进行重构,较之传统的Zernike多项式拟合方法,具有重构精度高且计算量小的特点。     

FBG分布式非均匀应变重构准确度分析研究

以剥层算法为基础,分别从非均匀解调应变大小、重构算法的特征参量以及光栅初始结构参量等对光纤布喇格光栅应变重构准确度的影响进行相关研究分析.结果表明:工作长度为5~30mm的光纤布喇格光栅最佳应变解调在3 000με以内,在该应变解调范围内,保持光栅剥层的分层长度为0.1mm左右时,应变重构准确度和效率较优,折射率调制幅度越小,应变重构误差越小;同时,对于非均匀应变检测使用的强光栅,折射率调制幅度约为0.000 12时,应变检测结果最好.本文的研究结果对提高非均匀应变的重构准确度具有重要的指导意义.     

改进的正交匹配追踪图像快速重建算法

传统采样需要的采样间隔小,当信号过长时会增加采样量,消耗过多的时间,占用更多的存储空间。提出了以Daubechies小波变换基作为稀疏变换基,用高斯随机矩阵作为观测矩阵,采用基于Dice匹配准则的正交匹配追踪算法作为恢复算法对图像进行重建。在分析了正交匹配追踪算法的特点后,提出了一种基于Dice匹配准则的改进的正交匹配追踪算法。该算法在原子匹配过程中将几何平均值用算术平均值替代,使重要成份在向量中的作用更加突出,能更准确地从字典中挑选出与残差向量最匹配的原子。仿真结果表明,该算法在相同的观测条件下,能减少重构误差,可将图像的重构质量提高2%左右,重构概率提高7%左右,有较高的应用价值。     

基于不可控微扫描的高分辨力图像重构方法

针对存在不可控微位移的序列低分辨力图像,提出了一种基于2×2不可控微扫描的高分辨力图像重构方法,采用投影法估算出低分辨力图像LR的微位移量,采用基于泰勒级数展开的重构算法由4帧图像重构高分辨力图像.模拟表明:该算法能精确地估计序列图像的帧间位移量并取得较好的重构效果,且算法简单有效可行,处理量小,有利于实现快速处理,在一定程度可满足同步轨道卫星、公安监视等领域对高分辨力成像处理的需求.     

基于信号子空间重构的鲁棒子区域Frost波束形成

本文针对一个感兴趣子区域内的宽带波束形成问题, 提出一种基于信号子空间重构的鲁棒Frost波束形成算法. 该算法的基本思想是利用一个矩阵滤波器从所估计的信号加干扰子空间中提取感兴趣信号(SOI)的特征分量; 然后利用该特征分量重构信号子空间; 最后利用重构的信号子空间构造一组线性约束最小方差(LCMV)准则, 来保证SOI近似无失真通过. 与现有的其他鲁棒Frost波束形成算法相比, 本文算法的一个显著优点是在未知SOI实际波达方向与频带等先验信息的情况下, 其导向与带宽均能够自适应地匹配SOI. 因此在整个感兴趣子区域内, 它都能获得接近最优值的输出信干噪比. 理论分析与仿真研究验证了算法的有效性.     

基于不可控微扫描的高分辨力图像重构方法

针对存在不可控微位移的序列低分辨力图像,提出了一种基于2×2不可控微扫描的高分辨力图像重构方法,采用投影法估算出低分辨力图像LR的微位移量,采用基于泰勒级数展开的重构算法由4帧图像重构高分辨力图像.模拟表明：该算法能精确地估计序列图像的帧间位移量并取得较好的重构效果,且算法简单有效可行,处理量小,有利于实现快速处理,在一定程度可满足同步轨道卫星、公安监视等领域对高分辨力成像处理的需求.       

三维空间二阶精度流体体积界面重构方法

给出三维空间网格模板含81个单元的最小二乘流体体积界面重构方法,并和Youngs方法及网格模板含125个单元的最小二乘流体体积界面重构方法进行比较.静态和动态的测试例子均表明:该方法能精确重构任意方向的平面界面,对C²光滑曲面它能达到二阶收敛精度.和网格模板含125个单元的最小二乘流体体积界面重构方法相比,在达到同样网格精度的条件下,减少了计算量,节省了计算时间,提高了计算效率.     

In situ investigation on rapid microstructure evolution in extreme complex environment by developing a new AFBP-TVM sparse tomography algorithm from original CS-XPCMT

A new sparse tomography method for observing the rapid internal microstructure evolution of material, called the Algebraic Filtered-Back-Projection and Total Variation Minimization (AFBP-TVM) iteration sparse reconstruction algorithm, was proposed in this paper. The new algorithm was developed by combining the two techniques of the Algebraic Reconstruction Technique (ART) and the Filtered-Back-Projection (FBP) on the basis of analysis in linear space. A series of numerical reconstruction experiments were conducted to validate the new algorithm. The results indicated the new algorithm can obtain satisfactory reconstruction images from 1/6 of the projections that were used in traditional algorithms. So the time spent on projection acquisition process can be reduced to 1/6 of that in traditional tomography method. The quality of images reconstructed by new algorithm was better than other algorithms, which was evaluated by three quantitative parameters. The normalized average absolute distance criterion and the normalized mean square criterion, which were used to evaluate the relative error of the reconstruction results (smaller value means better quality of reconstruction), decreased from 0.3758 to 0.1272 and from 0.1832 to 0.0894 respectively. The standardized covariance criterion, which was used to evaluate the similarity level (greater value means higher accuracy of reconstruction), increased from 92.72% to 99.30%. Finally, the new algorithm was validated under actual experimental conditions. The results indicated that the AFBP-TVM algorithm obtained better reconstruction quality than other algorithms. It meant that the AFBP-TVM algorithm may be a suitable method for in situ investigation on material's rapid internal microstructure evolution in extreme complex environment.     

基于双鸟群优化的高光谱图像非线性解混

针对高光谱图像像元中端元物质非线性混合的特点,借鉴生物群智能现象,提出一种基于双鸟群优化的高光谱图像非线性解混算法。为进一步提高非线性解混算法的精度,通过模拟鸟群中觅食、警惕以及飞行等行为得到非线性问题的最优解。算法通过双鸟群的迭代优化来交替更新目标函数中的最优解以及非线性模型参数,最终得到高光谱图像端元丰度的最佳估计。仿真实验和光谱数据实验结果表明:双鸟群优化算法迭代收敛,能克服局部最小值问题;相比于同类算法,该算法解混结果的丰度重建误差、平均光谱角距离和像元重建误差3项指标均较小,该算法解混精度高,像元重构效果好,能有效提高高光谱图像非线性解混的精度。     

利用声辐射模态重构任意目标的散射声场

水下目标散射声场的重构可以作为水下目标散射特性的研究基础。本文主要利用声辐射模态对水下目标进行散射声场重构研究。首先,在借助声传递矩阵给出的任意结构声辐射模态的流体域求解方法基础上,通过理论证明了目标的散射声压与声辐射模态具有函数关系。其次,借助声场分布模态的概念,同时考虑到声场分布模态病态及声压测量易受噪声污染,提出基于声辐射模态的正则化散射声场重构算法。仿真结果表明,波数越低,重构所需声辐射模态阶数越少,在较高波数时仅需总模态数的大约20%即可对声场进行重构。与基于边界元的声场重构算法相比,计算量减小了至少80%,且克服了赫姆霍兹积分方程最小二乘法仅对球壳结构的重构效果较好而不适用于长条形结构重构的缺陷。     

一种基于Radon逆变换的半覆盖螺旋锥束CT重建算法

半覆盖螺旋锥束计算机断层成像能够扩展传统螺旋锥束计算机断层成像的成像视野, 实现小面板探测器成像超视野物体. 但是, 各角度下的投影都存在数据截断, 会使重建结果中产生截断伪影, 降低图像质量. 本文提出了一种基于Radon逆变换的半覆盖螺旋锥束重建算法, 该算法在滤波时先使用局部算子, 再使用全局算子. 局部算子不受数据截断的影响, 并且降低了运算后的值由于数据截断所造成的不连续性, 因此, 减少了随后全局运算产生的截断误差. 仿真和实际实验结果均验证了本文算法的有效性. 和现有算法的对比也表明, 本文算法针对半覆盖螺旋锥束投影具有更强的截断伪影抑制能力, 能够有效提高重建图像的质量.     

FFT动态相位重建算法的滤波窗影响分析

为了优化相位重建算法,针对波面干涉图的傅里叶频谱,分析了不同滤波窗口的分布特征和频谱响应,通过计算机仿真和实验测试,确定了FFT动态相位重建算法的最佳滤波窗口类型。其中处理仿真干涉图重建的波面与原始波面的波面峰谷值残差为0.008 5λ,波面均方根值残差为0.000 1λ;处理实验干涉图获得的波面与移相干涉测量法获得的波面峰谷值残差为0.009 3λ,波面均方根值残差为0.000 5λ。结果表明:选取Hamming窗进行滤波处理并重建的相位经拟合后得到的波面较参考波面的面形残差最小,相位重建精度优于0.01λ,可进一步应用于大口径光学元件的测量中。     

An adaptive squared-distance-weighted interpolation for volume reconstruction in 3D freehand ultrasound

Volume reconstruction is a key procedure in 3D ultrasound imaging. An algorithm named as squared-distance-weighted (SDW) interpolation has been earlier proposed to reduce the blurring effect in the 3D ultrasonic images caused by the conventional distance weighted (DW) interpolation. However, the SDW parameter alpha, which controls the weight distribution, is a constant assigned by operators so that the interpolation effect is invariant for both sharp edges and speckle noises. In this paper, we introduced a new adaptive algorithm based on SDW interpolation for volume reconstruction of 3D freehand ultrasound. In the algorithm, the local statistics of pixels surrounding each voxel grid were used to adaptively adjust the parameter alpha in SDW. The voxel grids with a higher ratio of local variance and mean in their neighbourhoods would have a smaller alpha to make the image details sharper, while the voxel grids locating in regions with a lower ratio of local variance and mean would have a larger alpha to smooth image content in homogeneous regions, where speckle noise is usually observed and damages the image quality. By comparing the simulation results using the SDW and new adaptive algorithm, it was demonstrated that this new algorithm worked well in both edge preservation and speckle reduction.     

A new jet algorithm based on the k-means clustering for the reconstruction of heavy states from jets

A jet algorithm based on the k-means clustering procedure is proposed which can be used for the invariant-mass reconstruction of heavy states decaying to hadronic jets. The proposed algorithm was tested by reconstructing e⁺e^-→tt̄→6 jets and e⁺e^-→W⁺W^-→4 jets processes at using a Monte Carlo simulation. It was shown that the algorithm has a reconstruction efficiency similar to traditional jet-finding algorithms, and leads to 25% and 40% improvement of the top-quark and W mass resolution, respectively, compared to the k_T (Durham) algorithm. In addition, it is expected that the peak positions measured with the new algorithm have smaller systematical uncertainty.     

An improved gridding method for spiral MRI using nonuniform fast Fourier transform

The algorithm of Liu and Nguyen [IEEE Microw. Guided Wave Lett. 8 (1) (1998) 18; SIAM J. Sci. Comput. 21 (1) (1999) 283] for nonuniform fast Fourier transform (NUFFT) has been extended to two dimensions to reconstruct images using spiral MRI. The new gridding method, called LS_NUFFT, minimizes the reconstruction approximation error in the Least Square sense by generated convolution kernels that fit for the spiral k-space trajectories. For analytical comparison, the LS_NUFFT has been fitted into a consistent framework with the conventional gridding methods using Kaiser-Bessel gridding and a recently proposed generalized FFT (GFFT) approach. Experimental comparison was made by assessing the performance of the LS_NUFFT with that of the standard direct summation method and the Kaiser-Bessel gridding method, using both digital phantom data and in vivo experimental data. Because of the explicitly optimized convolution kernel in LS_NUFFT, reconstruction results showed that the LS_NUFFT yields smaller reconstruction approximation error than the Kaiser-Bessel gridding method, but with the same computation complexity.