提高关联成像重构质量的研究

比较基于压缩感知关联成像(CGI)与伪逆关联成像(PGI)两者之间的成像效果差异,探讨形态学权重自适应对关联成像去除噪声的效果。选择不同的图像,通过MATLAB软件开展仿真实验,对目标图像分别采样64、256、512、1 024、2 048、3 000次,首先通过关联成像、基于压缩感知关联成像与伪逆关联成像三种方法重构图像,再对比压缩感知与伪逆两种方法重构图像的效果,以峰值信噪比(PSNR)、相关系数(CC)为量化指标,将基于压缩感知关联成像与伪逆关联成像在不同采样次数下进行对比分析。同时,通过实验分析形态学权重自适应去除关联成像中噪声的效果。伪逆关联成像在低次数采样的情况下比基于压缩感知关联成像的成像效果更好,在高采样次数下,基于压缩感知关联成像的成像效果更好。在实际重构中压缩感知关联成像重构的图像仍有噪声,形态学权重自适应可以有效去除关联成像实验中产生的噪声。     

双臂对称性对压缩传感用于关联成像重构的影响

根据压缩传感理论和关联成像模型,将压缩传感理论应用于关联成像中,实现了传统的双臂关联成像的压缩传感重构。通过仿真实验验证了压缩传感用于关联成像的可行性,以峰值信噪比（PSNR）为衡量指标,分别对压缩传感和传统关联算法的重构图像质量进行了量化。仿真实验表明,压缩传感和关联算法的重构效果均随测量次数的增加而变优,在相同的测量次数下,压缩传感在关联成像中的重构图像的PSNR比传统的关联重构图像高20 dB以上。将压缩传感用于实际双臂关联成像的实验结果表明,压缩传感可以实现双臂关联成像装置的图像重构,但其重构质量很难优于传统关联算法的重构。针对这一实际实验与仿真实验似乎相矛盾的特殊现象,从双臂对称性的角度进行了合理解释,并利用实验中实际的散斑场对该现象进行了验证,最后提出了解决方案。     

基于压缩感知归一化关联成像实现目标重构

在归一化关联成像的基础上,结合压缩感知理论,提出了基于压缩感知的归一化关联成像方法。该方法首先对物臂的桶探测值进行归一化处理,并由散斑场构造测量矩阵;然后采用正交匹配追踪算法,在低测量次数下优质量地还原出了物体的像。实验中采用灰度图像及二值图像作为成像目标,以峰值信噪比作为衡量标准,分别对传统关联成像,归一化关联成像及压缩感知归一化关联成像的重构效果进行了量化对比。仿真实验结果表明,对于细节较为丰富的灰度图像,压缩感知归一化关联成像的峰值信噪比较传统方法高6dB左右,比归一化关联成像方法提高了2dB左右;对于细节较少的二值图像,其峰值信噪比较归一化关联成像法高3.4~4.3dB,比传统法高5.2~6.5dB。最后,采用实际电荷耦合元件测得的散斑场构造了测量矩阵,实验结果进一步验证了基于压缩感知的归一化关联成像算法能提高重构质量。     

基于压缩感知重构算法的关联成像系统研究

通过对关联成像原理的研究,提出了一种基于随机相位板的高效赝热光制备技术和基于压缩感知的图像重构算法,并最终搭建了等臂非预置的关联成像系统。实验结果表明,赝热光制备方法和压缩感知图像重构方法能够满足高质量关联成像系统要求。     

井下视频成像测井技术

井下视频成像测井利用井下摄像头获取井眼实时图像信息，可用于套管检测、落物打捞、井下作业质量检查等。文中采用基于小波变换的图像压缩技术、高速数字调制传输、基于CPLD的数字解调算法、特殊的井下仪器结构设计，解决了井下电视图像压缩，电缆高速数据传输，井下照明和保温等关键技术问题，设计出了井下电视成像测井仪样机，经过3000m电缆传输试验和125℃高温试验，仪器工作可靠、图像清晰稳定。     

低采样关联成像研究现状及发展

关联成像是一种基于光场二阶或高阶关联的主动间接成像技术,具有灵敏度高、抗干扰能力强等特点,在生物医学成像、遥感成像、海洋探测等领域有着重要的利用价值。然而,关联成像过程中对采样数的要求导致采样时间长、成像速度慢。如何在低采样的情况下获得高质量的图像重构依旧是关联成像在实际应用中需要解决的问题之一。详细阐述了关联成像的原理并介绍了近几年低采样关联成像的进展情况,如以深度学习为主的计算关联成像的理论及实验研究成果,并对关联成像的应用进行了总结和展望。     

基于小波变换的自主机器人运动目标检测研究

为解决动态目标识别技术在处理海量数据时间过长,难以满足实时性要求的问题。文中尝试用小波变换对图像进行压缩,并对压缩后的图像采用自适应阈值法进行分割处理,提取所需的轮廓信息部分,剔除不必要的背景。利用成像位置与行人位置的几何关系,以及位置和像素的关系,提出了一种简单算法,可快速判定动态目标与机器人之间的相对距离。     

并行压缩成像系统的压缩域小目标检测

提出一种适用于并行压缩成像系统的压缩域小目标检测算法,以便省去获得小目标位置信息时进行的图像重建环节,有效降低算法的复杂度。该方法通过并行压缩成像数学模型捕获背景以及待测图像压缩测量值,通过高斯混合模型进行压缩域背景建模,从而获得压缩域前景观测值。然后计算压缩域前景观测值与各压缩域目标位置模板的余弦相似度,根据局部阈值以及压缩域候选目标面积实现目标检测与定位。最后进行了仿真实验,分析了降采样率、测量次数、投影误差以及噪声等对目标检测效果的影响。结果表明:增大降采样率及噪声均会降低检测效果;测量次数对检测效果的贡献是有限的;测量次数为2次或3次时,可以在保证检测效果的同时有效控制运行时间。此外,噪声对检测效果影响较大,因而需要严格控制系统噪声。该方法可以在不进行任何图像重建的情况下实现目标的实时检测。     

互联网环境下语境分类目标信息分布式传播方法

传统的语境分类目标信息传播方法无法高效提升信息传播速度,提出一种互联网环境下语境分类目标信息分布式传播方法。互联网环境下,在语境中寻找关联因子,通过关联因子对所有信息进行分类;然后根据侦查到的信息找到目标信息,利用点模式匹配方法将所得到的目标信息进行关联,验证信息的特征层、分类层、综合信息和属性信息;最后根据侦查技术和成像技术对目标信息进行传播,由于语境信息种类不同,所以传播方式为分布式传播,传播层次可以分为图像信息层次传播、特征信息层次传播和关联信息层次传播。为检验该技术效果,与传统技术进行了实验对比,结果表明,所研究的分布式传播技术可以在短时间内完成分层次传播,工作效率更高,成本更低,对于信息发展有很好的促进作用。     

基于CS的SAR旋转微动目标检测方法研究

本文提出一种基于压缩感知理论(CS)实现旋转微动目标检测的方法。首先根据正侧视SAR系统空间几何模型对旋转点目标和旋翼三叶片目标进行成像;然后根据旋转微动目标的成像特征和形式,构造包含线形和圆形元素的超完备字典,再利用Hough变换域的稀疏性,用压缩感知理论寻找待检测图像中是否包含旋转目标所成像的几种形式来检测转动目标;最后通过补偿校正的方法对旋转微动目标进行再次判别,排除虚假目标。实验结果证明了所提方法的有效性。     

Turbidity-adaptive underwater image enhancement method using image fusion

Clear, correct imaging is a prerequisite for underwater operations. In real freshwater environment including rivers and lakes, the water bodies are usually turbid and dynamic, which brings extra troubles to quality of imaging due to color deviation and suspended particulate. Most of the existing underwater imaging methods focus on relatively clear underwater environment, it is uncertain that if those methods can work well in turbid and dynamic underwater environments. In this paper, we propose a turbidity-adaptive underwater image enhancement method. To deal with attenuation and scattering of varying degree, the turbidity is detected by the histogram of images. Based on the detection result, different image enhancement strategies are designed to deal with the problem of color deviation and blurring. The proposed method is verified by an underwater image dataset captured in real underwater environment. The result is evaluated by image metrics including structure similarity index measure, underwater color image quality evaluation metric, and speeded-up robust features. Test results exhibit that the method can correct the color deviation and improve the quality of underwater images.     

基于距离选通技术的水下目标成像系统研究

针对水下目标成像的特殊环境,提出将距离选通技术应用于水下目标的成像,距离选通技术对于减小水体后向散射光、水中微粒散射光,提高目标图像信噪比以及增加水下探测深度,是一种有效的方法。详细介绍距离选通水下目标成像系统的基本结构,以及系统关键部件的技术要求。实验表明:距离选通技术有效地提高了水下目标的成像质量。选通时间是影响成像质量的主要因素,单脉冲激光能量和水体衰减系数是影响系统探测深度的主要因素。     

时空过采样系统及其在点目标检测中的性能仿真

从成像探测体制出发,对过采样扫描系统的光学系统、电子学系统等模块分别进行了数学建模,并对点目标和场景图像进行了仿真实验。仿真过程中提出了一种对有限图像大量分割代替连续图像的建模思想和方法,在matlab环境中对源点目标图像和场景以及探测器扫描积分过程进行仿真,并对过采样图像进行图像融合。仿真结果给出了不同过采样倍数以及点目标位于不同相位时的信噪比变化和信噪比随积分时间增长的变化曲线。仿真结果表明,过采样探测系统融合后的图像虽然能够增大点目标在图像上的尺寸,但融合后的图像会增大高频噪声,造成检测概率降低,虚警率增大。文章最后给出了利用小孔模拟点目标成像的实验,进一步证实了仿真结果的正确性,说明时空过采样系统并不适合用于点目标检测。     

Attenuation correction in confocal laser microscopes: a novel two-view approach

Confocal microscopy is a three‐dimensional (3D) imaging modality, but the specimen thickness that can be imaged is limited by depth‐dependent signal attenuation. Both software and hardware methods have been used to correct the attenuation in reconstructed images, but previous methods do not increase the image signal‐to‐noise ratio (SNR) using conventional specimen preparation and imaging. We present a practical two‐view method that increases the overall imaging depth, corrects signal attenuation and improves the SNR. This is achieved by a combination of slightly modified but conventional specimen preparation, image registration, montage synthesis and signal reconstruction methods. The specimen is mounted in a symmetrical manner between a pair of cover slips, rather than between a slide and a cover slip. It is imaged sequentially from both sides to generate two 3D image stacks from perspectives separated by approximately 180° with respect to the optical axis. An automated image registration algorithm performs a precise 3D alignment, and a model‐based minimum mean squared algorithm synthesizes a montage, combining the content of both the 3D views. Experiments with images of individual neurones contrasted with a space‐filling fluorescent dye in thick brain tissue slices produced precise 3D montages that are corrected for depth‐dependent signal attenuation. The SNR of the reconstructed image is maximized by the method, and it is significantly higher than in the single views after applying our attenuation model. We also compare our method with simpler two‐view reconstruction methods and quantify the SNR improvement. The reconstructed images are a more faithful qualitative visualization of the specimen's structure and are quantitatively more accurate, providing a more rigorous basis for automated image analysis.     

A new nonlinear reconstruction method based on total variation regularization of neutron penumbral imaging

Neutron penumbral imaging is a significant diagnostic technique in laser-driven inertial confinement fusion experiment. It is very important to develop a new reconstruction method to improve the resolution of neutron penumbral imaging. A new nonlinear reconstruction method based on total variation (TV) regularization is proposed in this paper. A TV-norm is used as regularized term to construct a smoothing functional for penumbral image reconstruction in the new method, in this way, the problem of penumbral image reconstruction is transformed to the problem of a functional minimization. In addition, a fixed point iteration scheme is introduced to solve the problem of functional minimization. The numerical experimental results show that, compared to linear reconstruction method based on Wiener filter, the TV regularized nonlinear reconstruction method is beneficial to improve the quality of reconstructed image with better performance of noise smoothing and edge preserving. Meanwhile, it can also obtain the spatial resolution with 5 μm which is higher than the Wiener method.     

组合曝光的计算成像系统及其复原

传统光学成像方式在低照度条件下拍摄高速运动物体时,通过积分时间的配置难以平衡能量获取和高速运动模糊之间的矛盾.为了解决低照度条件下高速运动物体的清晰成像问题,本文提出一种基于组合曝光图像的计算成像方式,通过高帧频相机采集邻近两帧形成组合曝光图像对,基于两帧图像信息的互补,合理估算运动模糊点扩散函数,最终获取高信噪比的复...     

A non-convex regularization method combined with Landweber method for image reconstruction in electrical resistance tomography

Electrical resistance tomography (ERT) is a promising technique with which the conductivity distribution in the detected region can be visualized. Mathematically, the reconstruction of conductivity distribution is a seriously ill-posed inverse problem which poses a great challenge for the ERT sensing technique. The regularization method has been found to be an effective approach in coping with the inverse problem. In this work, a novel reconstruction strategy which combines the non-convex regularization method with Landweber method is proposed for the image reconstruction in ERT. At each iteration, the non-convex regularization is used to constrain the conductivity calculated with the Landweber method. A simple and efficient generalized iterated shrinkage algorithm is developed to solve the proposed method. To validate the performance of the proposed method, a series of numerical simulation is conducted and comparative analysis with other methods is performed. From the results, it can be observed that images with high quality are obtained when reconstructing with the proposed method. The impact of noise on the reconstruction is also investigated which shows that the images reconstructed by the proposed method are the least sensitive to the noise. The performance of the proposed method in the image reconstruction is also verified by experimental data. The results demonstrate that the inclusion is accurately reconstructed and the background is clear when the proposed method is adopted for the image reconstruction.     

基于贝叶斯自适应估计的光子计数集成成像

针对光子数极少环境下三维目标的重构问题,基于光子计数集成成像系统提出了一种贝叶斯自适应估计方法,来提高三维目标深度切片的重构质量。首先,通过光子计数集成成像系统获得一系列光子计数元素图像。接着,从光子计数过程的泊松分布出发,利用集成成像系统中对于同一个目标像素的多次采样特性,引入了局部自适应均值因子,从而建立起元素图像像素光子数估计的单参数后验概率模型。最后,通过后验概率模型的均值计算获得更新后的光子计数元素图像,并基于光束可逆原理重构出深度切片图像。实验结果表明:采用该方法在场景的两个深度处重构的切片图像相比传统贝叶斯重构图像的峰值信噪比提高了7.4dB和8.5dB,极大地提升了微弱光三维目标的重构质量。     

3D electromagnetic tomography using a single layer sensor array

Electromagnetic tomography (EMT) is a non-invasive technique to gain the induced voltages and to reconstruct the distribution of electromagnetic properties. A volume imaging using a single layer sensor array, namely, Single Layer 3D-EMT, has been developed in this paper. To solve the forward problem, three kinds of sensor arrays are established with different number of coils,—8, 12 and 16, to conduct simulations. Four typical conductivity distributions are used to verify the 3D-EMT imaging with single layer sensor array. The calculation of sensitivity maps in 3D views is presented, and the sensitivity maps of different layers, from z = 0 to z = 20, are analyzed. The conjugate gradient iterative method has been adopted in image reconstruction. It can be seen from the simulation results that the 3D reconstructed images using a single layer sensor array can display the distribution of the measured objects in position, shape, and size. By calculating the relative error, the quality of the reconstructed images is evaluated andthe result shows that the 12-coil sensor array has the best image quality among three sensor arrays. In addition, the single layer 3D experimental system has been established to evaluate the effectiveness of 3D imaging using a single layer sensor array. In order to save the hardware resources, the paper presents the author's research work about the possibility of Single Layer 3D-EMT imaging in simulations and experiments. This can also provide a guide to explore the potential application with electromagnetic testing technique.     

一种离子流束斑形状的快速检测方法

针对当前质谱仪研制及调试过程中离子束斑形状检测方法繁琐、效率低等问题,提出一种快速、实时的检测方法。该方法在传统刀边法的基础上,采用多角度切割线包围成图原理,即分别在0°、45°、90°、135°方向移动锋利刀边“切割”离子束,得出离子流强度变化曲线,最终还原离子束斑形状及束流核心区域。通过自行搭建的测试平台,将该方法得到的束斑形状与离子轰击痕迹法的结果进行对比,结果表明,采用本方法检测得到的离子束斑形状及核心区域与离子轰击痕迹法基本一致,但较后者操作简单、省时高效,可实现实时检测。