Convex relaxation based sparse algorithm for hyperspectral target detection

Target detection in hyperspectral images is an important task. In this paper, we propose a sparsity based algorithm for target detection in hyperspectral images. In sparsity model, each hyperspectral pixel is represented by a linear combination of a few samples from an overcomplete dictionary, and the weighted vector for such reconstruction is sparse. This model has been applied in hyperspectral target detection and solved with several greedy algorithms. As conventional greedy algorithms may be trapped into a local optimum, we consider an alternative way to regularize the model and find a more accurate solution to the model. The proposed method is based on convex relaxation technique. The original sparse representation problem is regularized with a properly designed weighted ?₁ minimization and effectively solved with existing solver. The experiments on synthetic and real hyperspectral data suggest that the proposed algorithm outperforms the classical sparsity-based detection algorithms, such as Simultaneous Orthogonal Matching Pursuit (SOMP) and Simultaneous Subspace Pursuit (SSP) and conventional ?₁ minimization.     

基于退火遗传算法的少数投影CT图像重建

不完全投影重建算法研究是当今图像重建算法中的一个难点问题，近年来，遗传算法在其中有一定的应用，但还存在一些问题。针对遗传算法在优化中的不足(如早熟收敛及易陷入局部最小等)，将模拟退火机制引入到遗传算子中，提出一种新的算法；并通过选择测试函数，建立将该算法应用于不完全投影图像重建的优化模型，进行计算机模拟。通过对从投影角间距为15°的12个不同投影视角方向获取的投影数据进行分析，结果表明，该算法的重建图像具有较高的精度。     

Iterative Multikinoform Method for Improving the Reconstruction of Kinoform

The authors proposed an interlacing technique (IT) approach for the synthesis of kinoform which uses a number of subkinoforms interlaced together into a multikinoform. Using the IT approach, the reconstructed image can be improved by optimizing each subkinoform with the general error-reduction algorithm. In this paper, they show a new iterative algorithm based on the IT, namely an iterative multikinoform method (IMM). After each of the subkinoforms is generated by the IT, the error image, which is the difference between the desired image and the sum of the images reconstructed from all subkinoforms, is circulated into an individual subkinoform to optimize each subkinoform so that the reconstruction error can be reduced further. This process can be performed on all subkinoforms iteratively. Simulation results show that the reconstruction error can be reduced further for kinoforms with larger quantization levels (larger than 2⁴) and its convergence is very rapid when the IMM is used.     

A six-dimensional approach to microtexture analysis

A mathematical framework is presented for microtexture derivation and analysis. A six-dimensional space is introduced, defined as the product of direct space (x, y, z) and orientation space, parametrized by the Rodrigues vector (r ₁, r ₂, r ₃). The framework is adapted to diffraction experiments, where orientation information from many grains or deformation microstructures is recorded in parallel, with the prime aim of allowing fast measurements and thus the ability to study microstructure dynamics. Assuming the use of a monochromatic beam the geometry of the projection surfaces is deduced. The derivation of the microtexture is formulated as an inverse problem similar to reconstruction problems in absorption or emission tomography. The applicability of the two major types of reconstruction algorithm, namely transform methods and algebraic methods, is discussed. An explicit solution in terms of the iterative algebraic reconstruction technique algorithm is given. The choice of basis function is discussed. Furthermore, the framework is applied to a number of important simplifying cases. These include grain-by-grain reconstruction, classical pole figure inversion and the generation of three-dimensional maps of non-deformed grains.     

A complex image reconstruction algorithm for real-time measurement of transient field

Optical CT is now expanding into reconstruction from few views or limited-view range projection considering the economy and practicality. To solve the conflict of velocity and precision, which are two main aims that image reconstruction algorithm pursued, an innovative complex image reconstruction algorithm for real-time measurement of transient field is proposed. This method reconstructs computerized tomography (CT) image firstly by frequency spectrum approach reconstruction technique (FSART) and then by modified simultaneous algebraic reconstruction technique (MSART) and can give a fast and precise reconstruction to complicated transient field.     

A categorization method of infrared polarization and intensity image fusion algorithm based on the transfer ability of difference features

The fusion of infrared polarization and intensity image can significantly improve the detection performance of target, and the fused image is more suitable for human visual perception and further image-processing tasks. In this paper, a new categorization method of infrared polarization and intensity image fusion algorithm based on the transfer ability of difference feature is proposed. Firstly, the difference feature between two kinds of image and the characteristics of different fusion algorithms are analyzed and summarized. Second, an evaluation vector of fusion algorithm for difference feature transform ability is constructed. Thirdly, the transfer ability of fusion algorithm for difference feature is estimated by the evaluation vector, and the degree of transfer ability of fusion algorithm for difference feature is analyzed. Finally the fusion algorithms are classified by the degree of transfer ability of fusion algorithm for difference feature. The results shows that the proposed fusion algorithm categorization method helps select fusion algorithms in actual scene.     

An iterative image reconstruction algorithm combined with forward and backward diffusion filtering for in‐line X‐ray phase‐contrast computed tomography

In‐line X‐ray phase‐contrast computed tomography (IL‐PCCT) can reveal fine inner structures for low‐Z materials (e.g. biological soft tissues), and shows high potential to become clinically applicable. Typically, IL‐PCCT utilizes filtered back‐projection (FBP) as the standard reconstruction algorithm. However, the FBP algorithm requires a large amount of projection data, and subsequently a large radiation dose is needed to reconstruct a high‐quality image, which hampers its clinical application in IL‐PCCT. In this study, an iterative reconstruction algorithm for IL‐PCCT was proposed by combining the simultaneous algebraic reconstruction technique (SART) with eight‐neighbour forward and backward (FAB8) diffusion filtering, and the reconstruction was performed using the Shepp–Logan phantom simulation and a real synchrotron IL‐PCCT experiment. The results showed that the proposed algorithm was able to produce high‐quality computed tomography images from few‐view projections while improving the convergence rate of the computed tomography reconstruction, indicating that the proposed algorithm is an effective method of dose reduction for IL‐PCCT.     

Convergence rate calculation of simultaneous iterative reconstruction technique algorithm for diffuse optical tomography image reconstruction: A feasibility study

Diffuse optical tomography (DOT) is an emerging technique for functional biological imaging. The imaging quality of DOT depends on the imaging reconstruction algorithm. The SIRT has been widely used for DOT image reconstruction but there is no criterion to truncate based on any kind of residual parameter. The iteration loops will always be decided by experimental rule. This work presents the CR calculation that can be great help for SIRT optimization. In this paper, four inhomogeneities with various shapes of absorption distributions are simulated as imaging targets. The images are reconstructed and analyzed based on the simultaneous iterative reconstruction technique (SIRT) method. For optimization between time consumption and imaging accuracy in reconstruction process, the numbers of iteration loop needed to be optimized with a criterion in algorithm, that is, the root mean square error (RMSE) should be minimized in limited iterations. For clinical applications of DOT, the RMSE cannot be obtained because the measured targets are unknown. Thus, the correlations between the RMSE and the convergence rate (CR) in SIRT algorithm are analyzed in this paper. From the simulation results, the parameter CR reveals the related RMSE value of reconstructed images. The CR calculation offers an optimized criterion of iteration process in SIRT algorithm for DOT imaging. Based on the result, the SIRT can be modified with CR calculation for self-optimization. CR reveals an indicator of SIRT image reconstruction in clinical DOT measurement. Based on the comparison result between RMSE and CR, a threshold value of CR (CR_T) can offer an optimized number of iteration steps for DOT image reconstruction. This paper shows the feasibility study by utilizing CR criterion for SIRT in simulation and the clinical application of DOT measurement relies on further investigation.     

非线性体效应的逆问题

非线性体效应在计算机断层扫描重构的理论与应用中,仍然是一个悬而未决的问题。本文利用优化重构算法来解决非线性体效应,建立了离散非线性X射线投影变换模型,将X射线投影变换的逆问题变为一个非凸的优化问题,通过裁剪原用于求解凸优化问题的一阶原对偶算法,提出非线性迭代重构算法来解决非凸问题。通过构建成像系统模型对算法的收敛性和重构精度进行了模拟验证,模拟中重建的图像首先通过检验在极窄的显示窗口中显示小于1%的对比度,然后使用相对于真实图像的差异的l2范数进行定量分析。模拟结果表明,在计算精度范围内,非线性重构算法可以收敛到真实图像,而且对于图像衬度小于1%的细节,重构图像也可以显示出来。该研究结果可为设计有效补偿非线性体效应伪影的计算机断层扫描成像应用算法提供参考。     

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.     

非相干照明条件下的ptychographic iterative engine成像技术

在传统多波长相干衍射成像理论的基础上提出适用于 X-射线和电子束等非相干光源照明成像的改进多波长ptychographic iterative engine 方法, 同时将小孔形状和照明光谱信息用于叠代计算, 可以在非相干照明条件下精确重建出物体的强度透射像和相位透射像, 并对光源带宽对重建精度的影响进行了分析, 对于解决如何在非相干照明条件下对大尺寸物体进行精确相位成像的问题具有较好的科研和实用价值.     

基于布拉格反射镜的X射线多色单能成像谱仪

报道了一种基于布拉格反射镜的多色单能成像谱仪研制工作,谱仪由针孔阵列、布拉格反射镜和CCD相机组成.大约有300个微孔的针孔阵列板置于布拉格镜前用于空间成像,通过布拉格反射镜的单色化,投射到CCD上的数百个小孔成像沿色散方向获得了能量分辨.经过图像处理,可以还原得到目标的多色单能二维成像.根据采用的布拉格分光元件和图像还原方法,谱仪的能量分辨达到了50—200（λ/Δλ）;针孔成像的空间分辨优于10 μm.同时还为该谱仪开发了专门的单能图像重建软件及图像数据后处理软件,可以在任意选择的窄能带内还原准单能图像.并重点介绍了该谱仪的优化设计、获得的技术指标以及专门研制的超短周期（2.5 nm）X射线W/B₄C多层镜. 关键词： X射线光学 诊断技术 布拉格反射镜 X射线多层镜     

跨界面目标电磁散射Sommerfeld积分的双重广义函数束拟合离散复镜像方法

混合势积分方程（mixed-potential electric field integral equation, MPIE）由于其Green函数的低阶奇异性是矩量法（MoM）等数值方法求解散射问题的主要方程.在跨界面目标的散射问题中,MPIE中的矢量势和标量势Green函数包含Sommerfeld类型的谱域积分,利用离散复镜像法（discrete complex image method, DCIM）和Sommerfeld恒等式,将其转化为有限项复镜像Green函数的求和运算,避免了烦杂的谱域积分运算. 关键词： Sommerfeld积分 离散复镜像法 广义函数束     

平场复用多焦点结构光照明超分辨显微成像

多焦点结构光照明显微技术(multifocal structured illumination microscopy, MSIM)能在50μm的成像深度内和1Hz的成像速度下实现两倍于衍射极限分辨率的提升,相比传统的宽场结构光照明显微技术,具有较大的成像深度和层析能力,更适合应用于厚样品的长时程三维超分辨成像.然而, MSIM存在成像速度慢、图像处理过程复杂等问题.本文提出了一种基于平场复用多焦点结构光照明的快速超分辨显微成像方法和系统(flat-field multiplexed MSIM, FM-MSIM),通过在照明光路中插入光束整形器件,将高斯光束转变为均为分布的平顶光束,提高激发点阵的强度均匀性和扩大视场;通过将每个衍射受限的激发点沿y方向延长,形成新的多路复用多焦点阵照明图案,提高能量利用率,减少扫描步数,进而提高成像速度和信噪比;结合基于多重测量矢量模型的稀疏贝叶斯学习图像重构算法,简化图像重构步骤,在保证空间分辨率的同时实现至少4倍于传统MSIM的成像速度.在此基础上,利用搭建的FM-MSIM系统进行了BSC细胞微管样片和小鼠肾切片标准样片的超分辨成像实验,实验结果证明...     

单母体遗传算法优化(H2O)n(n≤14)的结构

在传统遗传算法的基础上提出了单母体遗传算法(single-parent genetic algorithm, SPGA)，通过对母体团簇实施两种不同的变异操作对结构进行优化，给出了分子团簇结构优化的算法实现. 结合TIP3P模型势函数，研究了水分子团簇(H₂O)_n(n≤14)的稳定结构. 优化结构和已有理论及实验结果一致. 计算结果表明当n<8时，平均结合能随n增加较快；当n≥8时有小的起伏. n=4,8,10,12的团簇结构具有较高对称性，比较稳定. 关键词： 单母体遗传算法 水分子团簇 结构优化     

基于可能性信息质量合成的双模态红外图像融合算法选取

针对双模态红外图像在融合时异类差异特征两两合成出现信息冗余导致所选择的融合算法相互冲突,造成融合效果差甚至失效的问题,提出了一种基于可能性信息质量合成的双模态红外图像融合算法选取方法。首先计算双模态红外图像多融合算法下不同差异特征的融合有效度,利用可能性框架得到对应的可能性分布向量子集;其次计算向量子集的信息量和可信度,并对多个向量子集进行加权合成;然后构建基于信息质量的排序函数,得到每种融合算法下的非支配子集;最后构建多融合算法得分函数的联合分布对多种融合算法优化选择。实验结果表明,将基于质量来整合多个差异特征的方法运用于双模态红外图像融合算法选取中,所选出的融合算法在加权综合指标上高于其他算法均值55%以上,证明了本文方法的有效性和合理性;由多组实验算得本文方法平均耗时10.083 s,在时间效率上也符合实时图像融合应用的工程需求。     

An algorithm for sparse MRI reconstruction by Schatten p-norm minimization

In recent years, there has been a concerted effort to reduce the MR scan time. Signal processing research aims at reducing the scan time by acquiring less K-space data. The image is reconstructed from the subsampled K-space data by employing compressed sensing (CS)-based reconstruction techniques. In this article, we propose an alternative approach to CS-based reconstruction. The proposed approach exploits the rank deficiency of the MR images to reconstruct the image. This requires minimizing the rank of the image matrix subject to data constraints, which is unfortunately a nondeterministic polynomial time (NP) hard problem. Therefore we propose to replace the NP hard rank minimization problem by its nonconvex surrogate — Schatten p-norm minimization. The same approach can be used for denoising MR images as well.Since there is no algorithm to solve the Schatten p-norm minimization problem, we derive an efficient first-order algorithm. Experiments on MR brain scans show that the reconstruction and denoising accuracy from our method is at par with that of CS-based methods. Our proposed method is considerably faster than CS-based methods.     

稀疏阈值的超分辨率图像重建

为了解决基于字典学习的超分辨重构算法耗时过长的问题,提出了基于稀疏阈值模型的图像超分辨率重建方法。首先,将联合字典理论与图像块稀疏阈值方法相结合,训练得到高、低分辨率过完备图像字典对。接着,通过稀疏阈值OMP算法对图像特征块进行稀疏表示。然后,通过高分辨率字典重构出初始的超分辨图像。最后,通过改进迭代反投影算法对初始的超分辨图像进行全局优化,从而进一步提高图像重构质量。实验结果表明,超分辨图像重构平均峰值信噪比(PSNR)为30.1 d B,平均结构自相似度(SSIM)为0.937 9,平均计算时间为10.2 s。有效提高了超分辨重构的速度,改善了重构高分辨图像的质量。     

Exchange and nuclear symmetry interference in He+-He scattering

A method is described to determine the potential difference, V _g-V _u, that will accurately reproduce the exchange and nuclear symmetry oscillations observed by Aberth et al. in their experimental work on He⁺-He differential scattering. It is demonstrated that at higher energies and angles the experimental results for ⁴He⁺-⁴He, ⁴He⁺-³He and ³He⁺-³He appear incompatible with one another when investigated in terms of a two-state scattering theory. This is an indication that at these energies and angles the theory may require modification to include the effects of coupling to higher states.     

Genetic algorithms applied to neutron penumbral imaging

Penumbral imaging is a technique for imaging of neutrons or other penetrating radiations. The technique uses the fact that spatial information can be recovered from the shadow or penumbra that an unknown source casts of a simple large circular aperture. The limitation is that the straightforward image reconstruction will introduce some significant distortion for a large field of view because of non-isoplanaticity of the aperture point spread function. In this paper, a genetic algorithm (GA) is proposed for reconstruction of penumbral images and the technique allows distortion-free reconstruction over a large field of view. Furthermore, because in GA the complicateda priori constraints can be easily incorporated by appropriate modification of the cost function, the algorithm is also very tolerant of the noise.