数字图像相关方法中基于改进IC-GN算法高精度形变测量研究

在数字图像相关方法对物体形变测量中,FA-NR算法实现了高精度测量,IC-GN算法在此基础上提高了测量效率。为进一步提升测量精度,提出了一种基于IC-GN的改进算法(GIC-GN)。在已知整像素初始位置上,通过梯度法求得更准确的亚像素位移,减小Hessian矩阵计算过程中产生的误差,同时加快迭代的收敛速度,有效提高了测量精度和效率。仿真实验验证结果表明,GIC-GN算法误差能够稳定在10^-4～10^-3 pixel之间,对比IC-GN算法精度提升了10%～60%,耗时是FA-NR算法的0.1倍、IC-GN算法的0.8倍,能够实现对物体形变信息的高精度、高效率测量。     

基于虚拟相位平面的相位展开方法

在基于相位分析的三维测量系统中,为了准确地得到物体的高度,相位展开扮演着很重要的角色。传统的相位展开方法常常需要额外的投影图,而傅里叶变换轮廓术只需要采集一幅或两幅变形条纹图就可以实现对物体轮廓的测量,其方法速度快,易于实现。针对傅里叶变换轮廓术方法计算得到的截断相位分布,本文提出了一种利用截断相位与参考平面相位差值2π的整数倍数获得截断相位的正确级次,辅助相位展开的方法。当被测物体较复杂,或者相位截断次数较多时,该方法在已有参考平面相位的基础上虚拟新的相位平面,依次比较截断相位和虚拟相位,进行多次分级相位展开,结合多个展开相位结果,最终得到正确的展开相位。该方法展开速度快,展开错误不会蔓延传递。仿真和实物实验结果证明了该方法的可行性,说明该方法可用于傅里叶变换轮廓术中进行截断相位的快速展开。     

蛋白质微阵列SPR实时相位检测

将表面等离子体共振(surface plasmon resonance, SPR)与空间相位调制检测结合, 用一束准直的平行光照射传感芯片, 在反射光路中引入渥拉斯顿棱镜, 使光束中的p光和s光产生偏振光干涉形成条纹, 生化反应的有关信息从干涉条纹的相位变化中得出. 选择金膜厚度为30 nm和40 nm的两种芯片, 分别用浓度为50%和20%的酒精-水溶液进行实验, 得到SPR阵列图谱；选择金膜厚度为30 nm, 兔IgG作为阳性对照, 牛血清白蛋白(BSA)作为阴性对照, 与0.2 mL的羊抗兔IgG、1.8 mL水的混合溶液反应, 得到阵列反应图谱. 实验结果表明, 这种方法具有抗干扰能力强, 灵敏度高, 无需标记和可实时检测等优点, 能满足蛋白质芯片检测的要求.     

基于低相干干涉的透镜厚度测量及生物影像研究进展

低相干光干涉测量技术作为重要的非接触测量方法之一,由于具有结构简单、测量速度快及分辨率高的优点,在光学系统的非接触测量及生物医学影像等前沿领域具有广阔的应用前景。本文对透镜组的光学元件中心厚度及空气间隔的非接触测量技术进行了总结,简述了基于OCT的生物医学影像方面研究现状,重点论述基于低相干光干涉法测量原理和研究进展,对比分析相关研究方法的优缺点和创新之处,并从系统结构和应用范围的角度对低相干干涉测量技术的发展趋势作了展望。     

基于影像处理的子孔径拼接算法研究

大口径天文望远镜传递的影像信息是人们认识与了解宇宙的重要手段,因此大口径望远镜面形质量的好坏决定了系统的分辨率。本文介绍了检测大口径光学元件面形的一种方法,即子孔径拼接检测方法。首先分别检测元件各个子孔径的面形数据,最后通过影像处理算法复原面形信息。利用MATLAB软件进行了子孔径拼接算法的仿真,复原抛物面元件的面形。提出了利用数字影像处理和立体视觉影像的方法提高检测面形的精确度。展望了拼接后得到的面形的影像处理算法仍需考虑的因素,对后续研究提出新的挑战。     

基于适配体-金纳米粒子和光热-激光背向散射干涉技术的水中As(Ⅲ)的定量检测

针对As(Ⅲ)的检测问题,提出了一种基于适配体-金纳米粒子探针和光热-激光背向散射干涉原理的水中As(Ⅲ)的定量检测技术。结合了As(Ⅲ)适配体的金纳米粒子溶液呈现稳定的酒红色,对绿光有较强的吸收作用。采用532 nm的激光照射毛细管内的金纳米粒子溶液,由于光热效应溶液折射率发生变化,激光背向散射干涉(Back-Scattering Interference,BSI)产生的干涉条纹就会发生移动。待测溶液中存在As(Ⅲ)时,As(Ⅲ)与适配体相结合,导致适配体从金纳米粒子颗粒表面脱落,在高浓度盐的作用下,金纳米粒子颗粒聚集,溶液的颜色由酒红色变成蓝紫色,光热效应引起的干涉条纹移动量减小。建立As(Ⅲ)浓度与干涉条纹移动量之间的关系,通过检测干涉条纹的移动量实现了水中As(Ⅲ)的定量检测,检出限为0.127 mg/L。     

信息动态

信息时代的到来正在从各个方面对影像科学技术以及相关领域产生深刻影响,影像以及相关产业的形态也在发生着深刻的变化.建立在数字网络显示和CCD图像采集系统等基础上的影像信息及相关应用系统正在测量、监控、医疗、传感器、工业智能相机、工业自动化设备等领域广泛应用.因此,影像信息系统与处理在各个领域的相关研究具有重要的理论意义和工程意义.     

前言

正信息时代的到来正在从各个方面对影像科学技术以及相关领域产生深刻影响,影像以及相关产业的形态也在发生着深刻的变化。建立在数字网络显示和CCD图像采集系统等基础上的影像信息及相关应用系统正在测量、监控、医疗、传感器、工业智能相机、工业自动化设备等领域广泛应用。因此,影像信息系统与处理在各个领域的相关研究具有重要的理论意义和工程意义。     

大数值孔径光学镜约束多级衍射机理

针对基于激光照明的离轴全息显微成像系统存在散斑和寄生条纹噪声,以及基于部分相干光照明的离轴数字全息显微技术存在相干条纹对比度差的问题,本文提出了一种基于单色LED照明的衍射相位显微成像系统。该系统利用大数值孔径物镜及光栅对物光进行多级衍射,并采用4f系统和空间滤波器分离出0级和+1级信息,分别作为参考光和物光,最终两束光在CCD阵面上干涉产生离轴全息图,从而形成共光路全息成像结构。通过理论分析和计算,对实验用到的光学元器件进行选型,确保衍射光频谱信息能够分开且满足抽样条件。最后与传统激光离轴数字全息显微成像检测结果进行对比,实验结果表明,本文提出的系统能够获得较高的成像准确度和信噪比。     

机器视觉在光学加工检测中的应用

随着自动化控制领域的飞速发展,机器视觉技术日渐成熟,并且在各个领域赢得了越来越广泛的应用。机器视觉系统通过对图像信息的处理,用机器代替人眼实现了各种测量和判断。本综述简要介绍了机器视觉技术的概念和机器视觉系统的主要组成部分,阐述了机器视觉关键技术的发展现状,着重分析了机器视觉技术在光学加工检测领域,特别是在光学抛光检测过程中实现自动化的相关应用,最后展望了机器视觉在光学加工检测领域未来的发展趋势。     

Study of OSEM with different subsets in grating-based X-ray differential phase-contrast imaging

Impressive developments in X-ray imaging are associated with X-ray phase contrast computed tomography based on grating interferometry, a technique that provides increased contrast compared with conventional absorption-based imaging. A new "single-step" method capable of separating phase information from other contributions has been recently proposed. This approach not only simplifies data-acquisition procedures, but, compared with the existing phase step approach, significantly reduces the dose delivered to a sample. However, the image reconstruction procedure is more demanding than for traditional methods and new algorithms have to be developed to take advantage of the "single-step" method. In the work discussed in this paper, a fast iterative image reconstruction method named OSEM (ordered subsets expectation maximization) was applied to experimental data to evaluate its performance and range of applicability. The OSEM algorithm with different subsets was also characterized by comparison of reconstruction image quality and convergence speed. Computer simulations and experimental results confirm the reliability of this new algorithm for phase-contrast computed tomography applications. Compared with the traditional filtered back projection algorithm, in particular in the presence of a noisy acquisition, it furnishes better images at a higher spatial resolution and with lower noise. We emphasize that the method is highly compatible with future X-ray phase contrast imaging clinical applications.     

Atomic Level Characterization Based on Focus Modulation Electron Microscopy

Defocus image modulation processing and three-dimensional Fourier filtering methods are compared from the viewpoint of application to high-resolution phase transmission electron microscopy. Both methods can successfully correct the spherical aberration in TEM by image processing using through-focus images resulting in resolution improvement from the Scherzer resolution limit to the information limit. Comparing the processed images demonstrates that the potential to determine localized atomic structures between the two methods is at the same level when the sample thickness is thin. However, the achieved signal-to-noise ratio is better in images processed by the three-dimensional Fourier filtering method because the filtering process in Fourier space effectively reduces quantum noises involved in the original images. Spherical aberration-free phase observation by the latter method clearly shows the existence of individual gadolinium atoms in C₈₂ molecules encapsulated in single wall carbon nanotubes. It is demonstrated that the three-dimensional Fourier filtering method works effectively for atomic level characterization even when a sample consisting of light atoms is observed under the condition of a low electron dose.     

Image Enhancement—Chemical,Digital, Visual

Digital image processing has become well known through the high quality of some spectacular satellite images. It has developed into a discipline in its own right within information science and now finds application, not only in space travel, but also in such diverse fields as, for example, robotics, medical imaging, and television technology. Image processing also occurs, however, in photographic films and biological visual systems. In these systems, too, recorded images are manipulated for better recognition. This poses the question as to whether similar principles of image processing are operative in these different image handling systems.     

Design and performance of air flow-assisted ionization imaging mass spectrometry system

The imaging mass spectrometry（IMS） technology has experienced a rapid development in recent years.A new IMS technology which is based on air flow assisted ionization（AFAI） was reported.It allows for the convenient pretreatment of the samples and can image a large area of sample in a single measurement with high sensitivity.The AFAI in DESI mode was used as the ion source in this paper.The new IMS method is named AFADESI-IMS.The adoption of assisted air flow makes the sample pretreatment easy and convenient.An optimization of the distance between the ion transport tube and MS orifice increases the sensitivity of the system.For data processing,a program based on MATLAB with the function of numerical analysis was developed.A theoretical imaging resolution of a few hundred microns can be achieved.The composite AFAI-IMS images of different target analytes were imaged with high sensitivity.A typical AFAI-IMS image of the whole-body section of a rat was obtained in a single analytical measurement.The ability to image a large area for relevant samples in a single measurement with high sensitivity and repeatability is a significant advantage.The method has enormous potentials in the MS imaging of large and complicated samples.     

基于几何矩预分类的无人机遥感图像自动配准方法

图像配准技术是近些年来图像处理领域发展迅速的研究方向之一.在遥感领域内,图像配准更是实现图像融合、运动检测、图像校正、图像拼接等应用的一个关键步骤.尽管国内外目前在图像配准方面提出了很多方法,但不同方法适用的图像范围不同,很多时候需要人工干预进行方法的选择.尤其对于无人机这种快速、实时获取图像的新型遥感平台,如何集合不同方法的优点以实现图像自动配准成为了关键性问题.本文在比较分析了基于SIFT和SURF特征提取图像配准方法的各自优势后,提出基于几何矩的方法对图像进行预先分类,从而决定将其分配给何种方法进行配准,实现全程自动化.实验证明,这种图像自动配准方法在拓宽了图像应用范围的同时保证了良好的配准效果.     

Detection of non‐small cell lung cancer cells based on microfluidic polarization microscopic image analysis

In early diagnosis of lung cancer, a polarization microscopy is a powerful tool to obtain the optical information of biological tissues. In this paper, a new microfluidic polarization imaging and analysis method was proposed for the detection and classification of cancer‐associated fibroblasts and the two kinds of non‐small cell lung cancer cells, A549 and H322. A polarizing microscopy system was constructed based on a commercial microscope to obtain 3*3 Mueller matrix of cells. Based on the Muller matrix decomposition algorithm and analysis in spatial domain and frequency domain, appropriate classification parameters were selected for the characterization of different polarization characteristics of cells. Finally, the logistic regression models based on machine learning were applied to determine optimal feature parameters and classify cells. This method integrated the morphological information of the cells, and the polarization characteristics of the cells in different polarization states. It is for the first time that the polarization microscopic image analysis method has been applied to the detection and classification of non‐small cell lung cancer cells. The results show that the presented microfluidic polarization microscopic image analysis method could classify cells effectively. Compared with the Muller matrix measurement and calculation methods, the method proposed in this paper was greatly simplified in both the acquisition of polarized images and the analysis and processing of polarized images.     

基于分通道自适应匹配的梯度保持色彩迁移算法

本文针对经典Welsh与Reinhard算法进行改进，提出一种基于分通道自适应匹配的梯度保持色彩迁移算法。引入L、a、b三通道作为匹配依据，因通道间的序列不相关，对单一通道进行处理时不会影响到另外两通道，消除了RGB颜色模式中单一目标区域易受多通道影响的弊端；对整体灰度值相近的图像，将色度均值差异最大的待处理区与背景区通道及参考图像对应通道进行自适应匹配，解决了Welsh算法对灰度差异小或灰度范围重叠的彩色源图像分级易造成误判的问题。然后引入梯度因子，同参考图像与源图像标准差比值作加权运算，将结果作为本文改进迁移算法的缩放比例系数，对匹配到的每组像素采用保持梯度的色彩迁移算法进行着色，避免了Reinhard算法易出现色彩细节信息丢失、阶调间过渡不自然等问题。实验证明，本文改进算法所得目标图像的彩色化效果均优于经典Welsh与Reinhard算法，极大提升了色彩迁移算法的灵活性与适用性。     

A modified fuzzy C‐means algorithm using scale control spatial information for MRI image segmentation in the presence of noise

The fuzzy C‐means (FCM) algorithm does not fully utilize the spatial information for image segmentation and is sensitive to the presence of noise and intensity inhomogeneity in magnetic resonance imaging (MRI) images. The underlying reason is that using a single fuzzy membership function the FCM algorithm cannot properly represent pattern associations to all clusters. In this paper, we present a modified FCM (mFCM) algorithm by incorporating scale control spatial information for segmentation of MRI images in the presence of high levels of noise and intensity inhomogeneity. The algorithm utilizes scale controlled spatial information from the neighbourhood of each pixel under consideration in the form of a probability function. Using this probability function, a local membership function is introduced for each pixel. Finally, new clustering centre and weighted joint membership functions are introduced based on the local membership and global membership functions. The resulting mFCM algorithm is robust to the noise and intensity inhomogeneity in MRI image data and thereby improves the segmentation results. The experimental results on a synthetic image, four volumes of simulated and one volume of real‐patient MRI brain images show that the mFCM algorithm outperforms k‐means, FCM and some other recently proposed FCM‐based algorithms for image segmentation in terms of qualitative and quantitative studies such as cluster validity functions, segmentation accuracy and tissue segmentation accuracy. Copyright © 2015 John Wiley & Sons, Ltd.     

基于临近比较的快速拉曼光谱基线校正方法

拉曼光谱成像技术是基于拉曼散射效应所开发的一项现代检测技术,在现代生产、科学研究过程中使用非常广泛。拉曼光谱信号受荧光效应和仪器等方面的影响,往往会产生基线漂移,严重影响对信号特征的进一步提取。因此,必须对拉曼光谱信号进行基线校正。传统的基线校正方法,只针对单一光谱信号,计算量较大,在处理由大量拉曼信号组成的成像数据时,耗时较长且效果不佳。该文提出一种基于临近比较的快速基线校正方法,根据在相同背景下采集的光谱之间的相关性,实现快速基线校正,提高了拉曼成像数据的处理速度。     

A review of the CLIP system for the quantitative analysis of two-dimensional electrophoresis gels

This paper reviews the CLIP image processing system for the complete analysis of two-dimensional electrophoresis images. The analysis problem for two-dimensional gel images can be broken down into three issues: segmentation of individual gel images, alignment and comparison of pairs of gel images, and information storage and retrieval. This paper describes these problems and reviews how the CLIP system handles each of them. Segmentation is the location and isolation of each protein spot on an individual gel image and also the extraction of individual spot data such as position, area and volume. There are three basic stages: background field correction, noise filtering, spot detection and information extraction. Alignment and comparison of gel images involves matching protein spots between two gels. This can be quite difficult because there is not a simple relationship which can transform one gel image onto another. The database issues concern storing all the information which has been obtained from the above operations such that retrieval of this information can be readily performed. The advantage of the CLIP system over others is speed of processing. CLIP series computers use one processor for every pixel of the camera image such that image processing algorithms run in parallel. The main disadvantage is in the cost of these machines. With the declining trend in the cost of parallel processors, these machines will become more and more viable alternatives. This papers reviews the algorithms for the analysis of two-dimensional gels. It is shown that CLIP is flexible enough to perform more than one type of algorithm for a particular operation.