立体对电镜图像投射演示的原理和技术

要研究样品显微图像的三维信息,发展了立体电镜技术。立体对照片通常用反射立体镜观察。为适应在会议交流,可制成立体对幻灯片用幻灯机投射演示。立体对电镜图象投射演示在我国全国会议上以往未曾采用。本文论述其主要原理和技术。一、立体电镜术原理双眼视觉左眼看到物体的左侧多一些,右眼看到右侧的多一些。两个像的视差,在大脑被综合后获得第三维信息,即深度。立体电镜术是拍摄第一张图像后,将样品倾斜适当的角度拍摄第二张。这两张就成为立体对图像,见图1。     

利用图像翻转和复域编码的离轴干涉载频消除

提出一种利用图像翻转和复域编码消除离轴干涉载频影响,进而实现相位恢复的方法。方法通过旋转样品干涉图180,得到翻转干涉图。样品干涉图与翻转干涉图首先被复数域编码为一幅合成的干涉图。继而进行傅里叶变换,可通过带通滤波器提取频谱中相互分离的共轭项用于相位恢复。通过逆傅里叶变换,可以获得含有样品干涉图和翻转干涉图的相位分布、载频信息的结果。通过除法运算,载频得以在无需复杂运算、解包裹、系统先验信息的情况下被消除。通过仿真和实验验证了算法的可行性。实验结果表明该方法可获得精确的相位恢复结果。在恢复薄相位样品时,该方法的恢复时间仅为原图像翻转方法的23.32%。     

高分辨率扫描类电镜图像处理和分析测量系统

我们研制成功一套高分辨率的扫描类电镜用的图像处理系统,可直接连接到任一台扫描电镜(SEM)、电子探针(EPMA)、透射电镜(TEM)的扫描附件和扫描隧道显微镜(STM)等扫描类电镜(简称电镜)上采集电镜图像信号和样品成份的X射线面分布像的信号存入计算机。经系统的硬件软件作图像处理后,图像的清晰度,信噪比可得到提高(如图1所示)。本系统的图像分辨率为1024×1024像素点阵,具有256个灰度级的高质量电镜图像,达到国外高档电镜     

基于图像分割和盲反卷积的透射电镜图像漂移校正方法

样品漂移是影响透射电子显微镜分辨率的重要因素之一。近年来有一系列关于透射电镜图像漂移校正的算法，如Unblur、MotionCor和MotionCor2等，在冷冻电镜三维重构方面应用效果显著，但无法应用于材料表征电镜通常配备的CCD相机的图像漂移校正。本文提出了一种基于图像分割和盲反卷积的透射电镜图像漂移校正方法，在Goldstein和Fattal提出的利用功率谱的统计不规则性估计卷积核算法的基础上，利用图像分割解决了电镜图像样品部分和背景部分的运动方式不一致问题，能够应用于CCD相机的图像漂移校正。实验结果表明，本文的方法能够有效提高电镜图像的分辨率。     

冷冻电镜样品制备的生物安全评估

冷冻电镜是发现、鉴定病原微生物，解析病原微生物结构的有力工具。对冷冻电镜的实验过程中，样本是否会扩散到环境中导致污染，继而引发生物安全的问题，国内外目前都缺少相关实验探究。本研究利用当前广泛使用的直接投入式冷冻电镜样品制备设备，对病毒和细菌样品进行冷冻电镜样品制备，探究冷冻电镜制样过程中可能出现的样品泄露以及造成的污染问题，进行生物安全评估。实验结果表明：被滤纸吸附的样品可透过滤纸进一步污染制样设备，使用封口膜可有效避免样品进一步污染；病毒性样品实验结果表明即使用封口膜也可由多种原因而扩大污染范围。这些结果为冷冻电镜样品制备生物安全评估提供了实验依据。     

基于SU-8010场发射扫描电镜的个性化测试定制——管理者的实践与探索

探索不同类别样品的表征参数从而得到高品质的测试数据以及提高测试效率,是电镜管理者一直追求的目标。本文研制的场发射扫描电子显微镜样品快速定位系统,通过对每一个样品的精确定位,减少找样品的时间,使电镜使用效率提高13.6%;通过制备薄样品及减少电子束与基底材料的相互作用,相比传统分析方法,提高了纳米颗粒元素相对定量分析准确性;通过搭建导电通路、增加样品与导电胶接触面和不同的镀膜方式以及合适的探头选择,得到不导电厚样品的高清晰图像。此类研究可为电镜工作者提高管理质量提供一定参考。     

物联网技术在检验检测实验室管理中的应用研究

文中结合物联网技术的发展与应用现状,探讨了物联网技术在检验检测实验室管理中的应用。对物联网技术及检验检测实验室的发展现状及存在的问题进行了分析,在检验检测过程中,使用多种传感器获取实验室的各种信息(如射频信息、环境参数、高清全角度视频、实验仪器状态、样品参数等),通过局部的无线或有线网络等通信网路交互传递,实现对检测全过程的数据感知,经过信息智能接入检测平台的统一处理,最终通过物联网终端进行分布式呈现,实现实验室检验检测中的过程溯源、效率分析、质量管理和智能预警。     

自注意力引导的红外与可见光图像融合算法

为确保源图像中的显著区域在融合图像保持显著,提出了一种自注意力引导的红外与可见光图像融合方法。在特征学习层引入自注意力学习机制获取源图像的特征图和自注意力图,利用自注意力图可以捕获到图像中长距离依赖的特性,设计平均加权融合策略对源图像的特征图进行融合,最后将融合后的特征图进行重构获得融合图像。通过生成对抗网络实现了图像特征编码、自注意力学习、融合规则和融合特征解码的学习。TNO真实数据上的实验表明,学习到注意力单元体现了图像中显著的区域,能够较好地引导融合规则的生成,提出的算法在客观和主观评价上优于当前主流红外与可见光图像融合算法,较好地保留了可见光图像的细节信息和红外图像的红外目标信息。     

嵌入式Web远程监控实时系统设计与实现

针对目前监控管理自动化程度低、监控系统布线困难,传统方式较难实现远距离环境实时监测问题,提出了一种基于Arm+Linux+Web的自动化远程监控实时系统,可有效实现远程实时监控管理。首先,利用萤石云摄像提供的二次开发功能,完成图像信息的云端处理。然后,在下位机移植Arm-Linux操作系统,配置命令行统一资源定位器（commandLine uniform resource locator, CURL）的图像信息抓取应用,负责完成图像信息的本地化处理。最后,在上位机集成Web处理平台,完成Web图像信息显示功能。通过以上三个关键技术节点的集成,完成图像信息的Web实时显示。实验结果表明,所提方案能有效规避传统方式的弊端,取得了较好的实时监控效果。     

基于梯度图像融合的接触网绝缘子故障检测

针对单一红外图像或可见光图像不能够实现全天候检测的问题，提出了一种梯度图像融合模型将红外和可见光图像进行融合。先采用加速稳健特征算法（speeded-up robust features,SURF）将两幅图像的特征点进行匹配。接着采样剪切波变换（non-subsampled shearlet transform, NSST）算法将待融合图像进行分解，形成具有高频分量信息和低频分量信息的图，再分别对绝缘子的高频分量图和低频分量图进行融合，实现局部融合。利用NSST的逆变换对高频分量图和低频分量图进行逆变换，得到最终融合图，实现全局融合。对融合图像进行质量评价。采用最小二乘法直线拟合算法在二值图像的基础上来实现绝缘子的自爆检测；采用像素积分投影法来检测绝缘子片裂纹情况；采用颜色特征来检测绝缘子表面是否存在污秽的情况。通过实验对比单张图像和融合图像的检测结果的准确率。实验结果表明，采用基于融合图像的绝缘子自爆、绝缘子片裂纹、绝缘子表面污秽3个故障的识别率分别达到了95%、91%、90%，均高于单一的红外图像或可见光图像的识别率。     

A new way for multidimensional medical data management: volume of interest (VOI)-based retrieval of medical images with visual and functional features.

The advances in digital medical imaging and storage in integrated databases are resulting in growing demands for efficient image retrieval and management. Content-based image retrieval (CBIR) refers to the retrieval of images from a database, using the visual features derived from the information in the image, and has become an attractive approach to managing large medical image archives. In conventional CBIR systems for medical images, images are often segmented into regions which are used to derive two-dimensional visual features for region-based queries. Although such approach has the advantage of including only relevant regions in the formulation of a query, medical images that are inherently multidimensional can potentially benefit from the multidimensional feature extraction which could open up new opportunities in visual feature extraction and retrieval. In this study, we present a volume of interest (VOI) based content-based retrieval of four-dimensional (three spatial and one temporal) dynamic PET images. By segmenting the images into VOIs consisting of functionally similar voxels (e.g., a tumor structure), multidimensional visual and functional features were extracted and used as region-based query features. A prototype VOI-based functional image retrieval system (VOI-FIRS) has been designed to demonstrate the proposed multidimensional feature extraction and retrieval. Experimental results show that the proposed system allows for the retrieval of related images that constitute similar visual and functional VOI features, and can find potential applications in medical data management, such as to aid in education, diagnosis, and statistical analysis.     

Retrieval process of high-resolution HAADF-STEM images

A process for retrieving experimental high-resolution high-angle annular dark field (HAADF) scanning transmission electron microscopy (STEM) images, which are systematically distorted by environmental and/or instrumental instability in addition to the convolution influence of the probe, is demonstrated using a HAADF-STEM image of an antimony-rich basal plane inversion boundary in Sb2O3-doped ZnO ceramics recorded in the [0110] zone axis. The process includes a correction of the diffractogram of the HAADF-STEM image by referring to the diffractogram of a high-resolution transmission electron microscopy image of the same area. The corrected diffractogram is used for deconvolution processing combined with the maximum entropy method. The retrieved images show bright spots regarded as the object function. Thus, the processing of the experimental HAADF-STEM image provides almost a real projected atomic structure by reforming the systematic distortion and eliminating the effects of the probe function.     

Content-based retrieval of dynamic PET functional images

The recent information explosion has led to a massively increased demand for multimedia data storage in integrated database systems. Content-based retrieval is an important alternative and complement to traditional keyword-based searching for multimedia data and can greatly enhance information management. However, current content-based image retrieval techniques have some deficiencies when applied in the biomedical functional imaging domain. In this paper, we presented a prototype design for a content-based functional image retrieval database system for dynamic positron emission tomography (PET). The system supports efficient content-based retrieval based on physiological kinetic features and reduces image storage requirements. This design makes it possible to maintain a large number of patient data sets online and to rapidly retrieve dynamic functional image sequences for the interpretation and generation of physiological parametric images, and offers potential advantages in medical image data management and telemedicine, as well as providing possible opportunities in the statistical and comparative analysis of functional image data     

利用遗传编程排序图像

Web image retrieval is a challenging task. One central problem of web image retrieval is to rank a set of images according to how well they meet the user information need. The problem of learning to rank has inspired numerous approaches to resolve it in the text information retrieval, related work for web image retrieval, however, are still limited. We focus on the problem of learning to rank images for web image retrieval, and propose a novel ranking model, which employs a genetic programming architecture to automatically generate an effective ranking function, by combining various types of evidences in web image retrieval, including text information, image visual content features, link structure analysis and temporal information. The experimental results show that the proposed algorithms are capable of learning effective ranking functions for web image retrieval. Significant improvement in relevancy obtained, in comparison to some other well-known ranking techniques, in terms of MAP, NDCG@n and D@n.     

基于颜色和空间特征的彩色图像获取方法

本文针对基于内容的彩色图像相似性获取问题,提出了一种新的相似性获取方法,它既考虑了颜色内容特征,也包含了图像的空间关系特征.文章设计了无序矩阵来描述图像空间位置的相对关系,这种无序矩阵具有对旋转和平移不变性的特点.在进行图像间相似性测量时,首先用颜色直方图相交法对图像全局颜色分布进行相似性测量,再对得到的候选图像队列用新的算法进行测量,剔除不相似的图像.新的测量算法既考虑了颜色内容的匹配,同时也考虑了空间相似性的因素.用不同类型的图像对这种方法进行实验,其结果表明,它在彩色图像相似性检索时是很有效的,具有较高的检索精度.此外,它在图像发生小的旋转和平移等形变时,表现出较高的可靠性.     

A novel long-term learning algorithm for relevance feedback in content-based image retrieval

Relevance feedback has proven to be a powerful tool to bridge the semantic gap between low-level features and high-level human concepts in content-based image retrieval (CBIR). However, traditional short-term relevance feedback technologies are confined to using the current feedback record only. Log-based long-term learning captures the semantic relationships among images in a database by analyzing the historical relevance information to boost the retrieval performance effectively. In this paper, we propose an expanded-judging model to analyze the historical log data’s semantic information and to expand the feedback sample set from both positive and negative relevant information. The index table is used to facilitate the log analysis. The expanded-judging model is applied in image retrieval by combining with short-term relevance feedback algorithms. Experiments were carried out to evaluate the proposed algorithm based on the Corel image database. The promising experimental results validate the effectiveness of our proposed expanded-judging model.     

无卷边单分子层WS2纳米片原子结构的高分辨电子显微术研究

本文利用高分辨电子显微术(HRTEM)确定了无卷边的单分子层WS2纳米片的原子结构像.通过对样品不同区域HRTEM像进行傅里叶变换(FFT)分析,得到了各个区域的WS2纳米片的晶体取向,确定了WS2纳米片分子层数分布.根据电子显微像强度与样品层数的线性关系以及WS2纳米片的单分子层数分布模型,确定不同区域WS2纳米片的分子层数.为了进一步定量分析结果的正确性,通过模拟电子显微像在不同碳膜厚度及不同成像条件下WS2纳米片的HRTEM像,也确定了在像衬度上与实验像很好的匹配.     

Image indexing and retrieval using expressive fuzzy description logics

The effective management and exploitation of multimedia documents requires the extraction of the underlying semantics. Multimedia analysis algorithms can produce fairly rich, though imprecise information about a multimedia document which most of the times remains unexploited. In this paper we propose a methodology for semantic indexing and retrieval of images, based on techniques of image segmentation and classification combined with fuzzy reasoning. In the proposed knowledge-assisted analysis architecture a segmentation algorithm firstly generates a set of over-segmented regions. After that, a region classification process is employed to assign semantic labels using a confidence degree and simultaneously merge regions based on their semantic similarity. This information comprises the assertional component of a fuzzy knowledge base which is used for the refinement of mistakenly classified regions and also for the extraction of rich implicit knowledge used for global image classification. This knowledge about images is stored in a semantic repository permitting image retrieval and ranking. This research was supported by the European Commission under contract FP6-027026 K-SPACE.     

光强传输方程与图像插值融合的相位恢复

光强传输方程作为典型的相位恢复技术,在已知待测面光强分布与光强轴向微分时,可以通过求解该方程直接得到待测面的相位分布。强度微分可以通过采集沿传播方向的不同散焦面的光强信息以计算强度差分来估计,由此,散焦面的适当选择变得尤为重要。将光强传输方程与图像插值法相结合,在几何光学模型下描述采集的散焦面光强分布与聚焦面光强分布之间的关系,再利用图像插值法计算出模糊参数不同的散焦面的光强分布,由新得到的散焦图和采集的聚焦图代入光强传输方程以计算出相位。该方法只需要采集三幅强度图像,即可计算获得其他位置的强度图像,避免了采集设备的多次移动,也为某些特殊情况下无法获取适合位置的强度图像提供了一种解决途径。实验中搭建了一个实际的光强图像获取系统,所得结果验证了所提算法的有效性。