A nonlinear PDE model for reconstructing a regular surface from sampled data using a level set formulation on triangular meshes

In this paper, we propose a nonlinear PDE model for reconstructing a regular surface from sampled data. At first, we show the existence and the uniqueness of a viscosity solution to this problem. Then we propose a numerical scheme for solving the nonlinear level set equation on unstructured triangulations adapted to the data sample. We show the consistency of this scheme. In addition, we show how to compute nodewise first and second order derivatives. Some application examples of curve or surface construction are provided to illustrate the potential and to demonstrate the accuracy of this method.     

Point-wise hierarchical reconstruction for discontinuous Galerkin and finite volume methods for solving conservation laws

We develop a new hierarchical reconstruction (HR) method  and  for limiting solutions of the discontinuous Galerkin and finite volume methods up to fourth order of accuracy without local characteristic decomposition for solving hyperbolic nonlinear conservation laws on triangular meshes. The new HR utilizes a set of point values when evaluating polynomials and remainders on neighboring cells, extending the technique introduced in Hu, Li and Tang [9]. The point-wise HR simplifies the implementation of the previous HR method which requires integration over neighboring cells and makes HR easier to extend to arbitrary meshes. We prove that the new point-wise HR method keeps the order of accuracy of the approximation polynomials. Numerical computations for scalar and system of nonlinear hyperbolic equations are performed on two-dimensional triangular meshes. We demonstrate that the new hierarchical reconstruction generates essentially non-oscillatory solutions for schemes up to fourth order on triangular meshes.     

基于全变分正则化的高能闪光照相消模糊图像重建算法

 针对高能闪光照相投影图像消模糊难度大的问题,提出了一种基于全变分正则化的消模糊图像重建算法,该算法根据闪光照相的成像特点,将客体的纵向截面作为一个整体来进行建模,并在重建方程中考虑了模糊因素,然后采用全变分范数作为正则项,构建了用于消模糊图像重建的展平泛函,将消模糊图像重建问题转化为能量泛函极小化问题,通过固定点迭代算法求解图像重建问题的最小化解。数值模拟结果表明：该算法由于考虑了闪光照相成像时的图像模糊因素,在重建时能够较好地消除模糊对重建结果的影响,在抑制噪声的同时能较好地保持图像的边缘信息,有利于提高重建图像的质量。     

基于小波域马尔可夫随机场模型的压缩传感图像重构

目前在压缩传感重构算法中利用图像的可稀疏性表示先验知识,从比奈奎斯特采样少得多的观测值中恢复原始图像。除了稀疏性之外,邻域系数的相关性也可以作为先验知识加速重构算法收敛。为了克服目前算法中没有利用邻域系数相关性的缺点,提出了基于小波域马尔可夫随机场模型的压缩传感图像重构算法,根据显著性度量对变换系数进行分类得到具有马尔可夫性的初始掩模,利用ICM算法完成掩模优化,实现系数更新,并将算法与未考虑邻域相关性的算法进行了比较。实验结果证明了算法的有效性。     

螺旋锥束CT中两种解析重建算法的研究

 研究了锥束螺旋Katsevich和FDK重建算法,并对这两种算法进行比较。实验结果表明：当投影数据没有噪声的时候,FDK算法和Katsevich算法均能取得较好的效果,当对实际物体进行重建的时候,投影数据含有噪声, Katsevich算法需要对投影数据求导,而它对投影数据的噪声较敏感,重建质量有所下降。     

Wavelet-based edge correlation incorporated iterative reconstruction for undersampled MRI

Undersampling k-space is an effective way to decrease acquisition time for MRI. However, aliasing artifacts introduced by undersampling may blur the edges of magnetic resonance images, which often contain important information for clinical diagnosis. Moreover, k-space data is often contaminated by the noise signals of unknown intensity. To better preserve the edge features while suppressing the aliasing artifacts and noises, we present a new wavelet-based algorithm for undersampled MRI reconstruction. The algorithm solves the image reconstruction as a standard optimization problem including a ?₂ data fidelity term and ?₁ sparsity regularization term. Rather than manually setting the regularization parameter for the ?₁ term, which is directly related to the threshold, an automatic estimated threshold adaptive to noise intensity is introduced in our proposed algorithm. In addition, a prior matrix based on edge correlation in wavelet domain is incorporated into the regularization term. Compared with nonlinear conjugate gradient descent algorithm, iterative shrinkage/thresholding algorithm, fast iterative soft-thresholding algorithm and the iterative thresholding algorithm using exponentially decreasing threshold, the proposed algorithm yields reconstructions with better edge recovery and noise suppression.     

基于径向基神经网络预测的混沌时间序列嵌入维数估计方法

根据Takens定理,研究了混沌时间序列相空间重构嵌入维数的选取问题.提出了基于径向基函数神经网络预测模型性能的嵌入维数估计方法,即根据嵌入维数与混沌时间序列预测模型性能的变化关系来确定嵌入维数.通过对几种典型混沌动力学系统的数值验证,结果表明该方法能够确定出合适的相空间重构嵌入维数. 关键词： 混沌 相空间重构 嵌入维数 预测     

无零级衍射干扰的彩色数字全息研究

彩色数字全息研究中,用球面波为重建波及角谱衍射公式进行波前重建是一种有效的方法.然而,重建图像上通常伴有强烈的零级衍射干扰.本文通过理论分析,对波前重建过程作了重要改进.用改进后的方法进行彩色数字全息的实验研究表明,重建彩色图像的质量获得显著改善. 关键词： 彩色数字全息 波前重建 零级衍射干扰     

基于解耦差分泽尼克待定系数法的二维横向剪切波面重建算法

横向剪切干涉术是一种自参考干涉计量技术,其原理是被检测波前与其自身被剪开的波前之间在重叠范围内相干涉,由干涉图得到两相互剪切波前的波前差,通过波面重建算法得到待测波面.在波面重建算法中,泽尼克待定系数法是其中的一种.分析了横向剪切干涉技术的测量原理;提出了一种新的基于解耦差分泽尼克待定系数法的二维横向剪切波面重建算法....     

一种测量多相流流型的ECT图像重建算法

提出了一种新的电容层析成像图像重建算法-IMNSNOF算法.该算法在分析极小范数解的基础之上针对ECT逆问题的特点对其进行改进,并利用奇异值分解定理证明这种改进的数值稳定作用.在此基础上建立新的日标泛函,并在求解该泛函的过程中采用正则技巧对其进行改进确保数值解的稳定性.利用非闭合电极ECT传感器实测了多相流沿流向的流型...