基于主动位移成像的图像超分辨率重建

超分辨重建算法是一种将低分辨率图像恢复为高分辨率图像的算法,被广泛用于医学、遥感、军事安防以及人脸识别等领域。在黑夜、远场场景下构建数据集比较困难,基于深度学习的超分辨重建算法应用受到阻碍。而微扫描成像技术扫描模式固定,对器件到位精度要求高。针对这两个问题,我们提出一种基于主动位移成像的图像超分辨率重建算法。具体地,在控制相机随机移动的同时记录采样时刻位移,通过解算、映射选图、精确匹配图像序列并获取多帧图像间的亚像素信息,然后对估计图像进行迭代和更新,最后重建获得高分辨率图像。实验结果表明,本算法在PSNR、SSIM和平均梯度三个指标上都优于最近提出的基于POCS的图像超分辨率重建算法MFPOCS,与基于CNN的方法 ACNet相比具有竞争力。值得提出的是,本算法无需固定的扫描模式,降低了微扫描技术对器件实时到位精度的要求,同时,本算法可以保证重建初始帧的优良选取,有效规避了POCS算法的固有缺点。     

基于HUBER函数的序列图像位移场估计算法

提出了一种基于Huber函数的序列图像位移场估计算法，与光流法不同的是，它能直接计算位移场，还能在一定程度上减轻对于变化剧烈的“运动边界”过渡平滑的问题，该算法采用共轭梯度法优化能量方程，并利用小波分解进行分级计算，能快速可靠地得到稳定的位移场，实验表明，对有较大弹性形变的图像，与块匹配法相比，该算法得到的平均匹配残差明显减少。     

运用稀疏表示法进行单幅图像超分辨的内点方法

稀疏表示法在单幅图像超分辨率重建问题中受到广泛的关注.本文介绍了一种使用稀疏表示进行超分辨率图像重建的方案.该方案首先由低分辨率的输入图像块求取稀疏表示系数,然后根据此系数生成对应的高分辨率图像块,最后由高分辨率块重建出整幅图像.在求取稀疏表示系数时,本文采用了一种借助预处理共轭梯度算法计算搜索方向的内点方法.仿真结果...     

基于稀疏表示和自适应字典学习的“高分一号”遥感图像去噪

对高分辨率遥感图像进行去噪是遥感研究中的一个重要难题。本文提出了一种新的基于稀疏表示的高分辨率遥感图像去噪算法,该算法根据加噪高分辨率遥感图像的特点利用 K-SVD 算法自适应的学习得到能高效描述遥感图像内容的字典,利用稀疏表示实现去噪,并且保留原图像的有用信息。通过对“高分一号”获取的遥感图像进行实验表明,该算法能较好地滤除遥感图像的噪声,提高了图像的峰值信噪比,该方法比其他字典学习算法及其他去噪算法具有更好的性能。     

利用二维插值核的高分辨力图像重构

利用连续图像采样及其内插公式,提出了一种基于二维插值核重建高分辨力图像的新算法。该算法先使一般低分辨力序列图像具有标准位移关系,再根据高、低分辨力图像之间的关系重构高分辨力图像。同时利用正则化技术导出了一套重复迭代算法,以提高算法的处理效果和克服病态问题。实验表明,该算法使图像的细节和清晰度大大增强,分辨力大幅度提高,明显优于零阶保持插值算法的处理结果,其峰值信噪比提高8-9dB。     

一种基于MOD字典学习的图像超分辨率重建新算法

将低分辨率图像重建成高分辨率图像是图像处理领域中的一个重要课题。Yang提出一种基于联合字典学习的图像超分辨率重建算法,其算法样本选取与字典训练方法较为复杂。提出一种基于MOD字典学习的图像超分辨率重建新算法,首先采用少量的训练样本代替Yang的大量训练样本,然后使用MOD字典学习算法代替Yang的FFS字典学习算法,最后利用字典对图像进行稀疏表示与重建。实验结果表明,所提出的算法速度较快,并且重建图像的质量较高。     

超分辨率图像重建在法庭科学中的应用

超分辨率图像重建是近年来迅速发展起来的一种旨在利用某一景物的若干低分辨率图像获取该景物高分辨率图像的技术。本文介绍了超分辨率图像重建技术在法庭科学中的应用、作用、方法,并总结了相关问题和发展方向。     

像素灰度值独立方程重构高分辨力图像

为了提高图像空间分辨力,提出一种基于像素灰度值独立方程重构高分辨力图像的技术.采用机械微扫描法获取序列低分辨力图像,分析半像素错位的序列低分辨力图像与高分辨力图像各像素灰度值的对应关系,建立了高分辨力图像的像素灰度值独立方程,并利用像素灰度值独立方程重构高分辨力图像.仿真结果表明,相比于反演解析法,基于像素灰度值独立方程的重构算法把重构时间从秒级提高到毫秒级,为重建高分辨力视频信号奠定了基础.     

基于改进梯度向量流形变模型的动目标检测方法

针对现有图像序列动目标检测技术抗噪声能力较差、跟踪性能鲁棒性不强的不足,提出了一种改进的梯度向量流形变模型算法,该算法构造了新的梯度向量场,利用图像灰度梯度信息、帧间运动信息以及邻域灰度信息相结合进行梯度向量场计算.仿真试验结果表明,该方法较好地克服了图像序列中随机噪声的影响,计算出的梯度向量场基本没有干扰区域,同传统向量场相比较,有效地提高了算法的抗噪能力和跟踪结果的准确性,可更好地实现图像序列的动目标检测.     

多正则化形式的超分辨率图像重建

为了抑制超分辨图像重建过程中的振铃锯齿效应,本文提出一种多正则化形式的超分辨率重建算法。文章首先给出了图像降质模型并推导出了图像重构约束项。利用重构项直接对低分辨率图像进行重建,获得的高分辨图像会有锯齿和振铃效应。针对此问题,本文利用自回归模型和滤波器组先验来正则化重建过程。自回归模型用来恢复图像局部细节描述,与此同时本文利用自然图像块的聚类集来估计自适应自回归模型参数。滤波器组先验用来约束重建图像的边缘,使得获取的高分辨率的图像边缘更加锐利。最后通过实验定性与定量的分析,证实了本文算法优于其他具有竞争力的算法。     

An iterative synthetic aperture imaging algorithm with correction of diffraction effects

In this paper we present an iterative version of the synthetic aperture imaging algorithm extended synthetic aperture technique (ESAFT) proposed recently. The algorithm is based on a linear model that accounts for the distortions effects of an imaging system used for acquisition of ultrasonic data. Improved resolution (both lateral and temporal) in the reconstructed image is obtained as a result of minimizing the reconstruction mean square error. In this work, the minimization is extended to parameters that characterize expected amplitudes of each image element in the area of interest. An iterative optimization scheme is proposed, which in each step performs minimization of the reconstruction error based on the parameter matrix found in the previous step. Comparing to ESAFT, the proposed approach yields a significant improvement in resolution and a high degree of robustness with regard to initial choice of the parameter matrix. Performance of the proposed algorithm is evaluated using both real and simulated ultrasonic data.     

Continuous-wave terahertz phase imaging using a far-infrared laser interferometer

Terahertz phase imaging can reveal the depth information of an optically opaque object and provide much better contrast for weak-absorption materials. We demonstrate a continuous-wave terahertz interferometric imaging method in which a far-infrared laser interferometer is used to measure the phase distribution with diffraction-limited lateral resolution and subwavelength axial resolution. An improved four-step phase-shifting algorithm is introduced to retrieve the phase map with very high accuracy and low distortion. The relative depth profiles of two transparent samples are successfully extracted by using this method. Experimental results verify that terahertz interferometric imaging in combination with the phase-shifting technique enables effective reconstruction of the phase image of the object under test.     

Infrared image registration and high-resolution reconstructionusing multiple translationally shifted aliased video frames

Forward looking infrared (FLIR) detector arrays generally produce spatially undersampled images because the FLIR arrays cannot be made dense enough to yield a sufficiently high spatial sampling frequency. Multi-frame techniques, such as microscanning, are an effective means of reducing aliasing and increasing resolution in images produced by staring imaging systems. These techniques involve interlacing a set of image frames that have been shifted with respect to each other during acquisition. The FLIR system is mounted on a moving platform, such as an aircraft, and the vibrations associated with the platform are used to generate the shifts. Since a fixed number of image frames is required, and the shifts are random, the acquired frames will not fall on a uniformly spaced grid. Furthermore, some of the acquired frames may have almost similar shifts thus making them unusable for high-resolution image reconstruction. In this paper, we utilize a gradient-based registration algorithm to estimate the shifts between the acquired frames and then use a weighted nearest-neighbor approach for placing the frames onto a uniform grid to form a final high-resolution image. Blurring by the detector and optics of the imaging system limits the increase in image resolution when microscanning is attempted at sub-pixel movements of less than half the detector width. We resolve this difficulty by the application of the Wiener filter, designed using the modulation transfer function (MTF) of the imaging system, to the high-resolution image. Simulation and experimental results are presented to verify the effectiveness of the proposed technique. The techniques proposed herein are significantly faster than alternate techniques, and are found to be especially suitable for real-time applications     

Image reconstruction with a shift‐variant filtration in circular cone‐beam CT

It is well known that cone‐beam data acquired with a circular orbit are insufficient for exact image reconstruction. Despite this, because a cone‐beam scanning configuration with a circular orbit is easy to implement in practice, it has been widely employed for data acquisition in, e.g., micro‐CT and CT imaging in radiation therapy. The algorithm developed by Feldkamp, Davis, and Kress (FDK) and its modifications, such as the Tent–FDK (T‐FDK) algorithm, have been used for image reconstruction from circular cone‐beam data. In this work, we present an algorithm with spatially shift‐variant filtration for image reconstruction in circular cone‐beam CT. We performed computer‐simulation studies to compare the proposed and existing algorithms. Numerical results in these studies demonstrated that the proposed algorithm has resolution properties comparable to, and noise properties better than, the FDK algorithm. As compared to the T‐FDK algorithm, our proposed algorithm reconstructs images with an improved in‐plane spatial resolution. © 2005 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 14, 213–221, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ima.20026     

数字化电容层析成像系统

基于电容敏感原理设计的数字化电容层析成像（ECT）系统，利用有限元法，分析了阵列电极结构对敏感场分布的影响，通过优化设计和仿真试验，改善了敏感场分布的均匀性；构建了以数字信号处理器（DSP）为核心、现场可编程门阵列（眦）协同工作的12电极的数字化ECT系统，提出了由离线预迭代和在线一步成像所构成的新的图像重建算法——预迭代法，其成像速度及精度均明显得到提高。     

三维高分辨工业X-CT系统

介绍了采用高分辨CCD面阵列探测器的微焦点三维CT系统的基本结构，应用基于Feldkamp的近似三维重建算法获得了令人满意的图像质量，与以往用线阵列探测器的CT系统比较，该系统具有采集数据快，成像速度快，检测周期短的特点，可实现对被检测陶瓷样品100％的检测，给出了使用该系统检测陶瓷轴承球的DR（数字照相）及CT图像。     

基于lp范数的ECT图像重建算法研究

针对在ECT图像重建过程中,基于lp-范数的非凸压缩感知算法常存在计算量较大以及现有的近端映射算法受一些特定的p值限制而导致成像分辨率较低的问题,利用改进的插值函数替换lp-范数xpp,通过调整参数使得改进的函数无限逼近lp-范数xpp,同时引入阈值表示理论,并在此基础上提出新的自适应阈值迭代算法对新模型进行求解。实验结果表明,改进后的自适应lp-范数重构算法相对于Landwebr算法、迭代重加权最小二乘法具有更强的适应性,更高的图像分辨率,更快的成像速度。     

A new coded-excitation ultrasound imaging system. I. Basicprinciples

A new approach to ultrasound imaging with coded-excitation is presented. The imaging is performed by reconstruction of the scatterer strength on an assumed grid covering the region of interest (ROI). Our formulation is based on an assumed discretized signal model which represents the received sampled data vector as a superposition of impulse responses of all scatterers in the ROI. The reconstruction operator is derived from the pseudo-inverse of the linear operator (system matrix) that produces the received data vector. The singular value decomposition (SVD) method with appropriate regularization techniques is used for obtaining a robust realization of the pseudo-inverse. Under simplifying (but realistic) assumptions, the pseudo-inverse operator (PIO) can be implemented using a bank of transversal filters with each filter designed to extract echoes from a specified image line. This approach allows for the simultaneous acquisition of a large number of image lines. This could be useful in increasing frame rates for two-dimensional imaging systems or allowing for real-time implementation of three-dimensional imaging systems. When compared to the matched filtering approach to similar coded-excitation systems, our approach eliminates correlation artifacts that are known to plague such systems. Furthermore, the lateral resolution of the new system can exceed the diffraction limit imposed on conventional imaging systems utilizing delay-and-sum beamformers. The range resolution is compared to that of conventional pulse-echo systems with resolution enhancement (our PIO behaves as a pseudo-inverse Wiener filter in the range direction). Both simulation and experimental verification of these statements are given     

Non-Local DWI Image Super-Resolution with Joint Information Based on GPU Implementation

Since the spatial resolution of diffusion weighted magnetic resonance imaging (DWI) is subject to scanning time and other constraints, its spatial resolution is relatively limited. In view of this, a new non-local DWI image super-resolution with joint information method was proposed to improve the spatial resolution. Based on the non-local strategy, we use the joint information of adjacent scan directions to implement a new weighting scheme. The quantitative and qualitative comparison of the datasets of synthesized DWI and real DWI show that this method can significantly improve the resolution of DWI. However, the algorithm ran slowly because of the joint information. In order to apply the algorithm to the actual scene, we compare the proposed algorithm on CPU and GPU respectively. It is found that the processing time on GPU is much less than on CPU, and that the highest speedup ratio to the traditional algorithm is more than 26 times. It raises the possibility of applying reconstruction algorithms in actual workplaces.