Near-field 3D imaging approach combining MJSR and FGG-NUFFT

A near-field three-dimensional(3 D)imaging method combining multichannel joint sparse recovery(MJSR)and fast Gaussian gridding nonuniform fast Fourier transform(FGGNUFFT)is proposed,based on a perfect combination of the compressed sensing(CS)theory and the matched filtering(MF)technique.The approach has the advantages of high precision and high efficiency:multichannel joint sparse constraint is adopted to improve the problem that the images recovered by the single channel imaging algorithms do not necessarily share the same positions of the scattering centers;the CS dictionary is constructed by combining MF and FGG-NUFFT,so as to improve the imaging efficiency and memory requirement.Firstly,a near-field 3 D imaging model of joint sparse recovery is constructed by combining the MF-based imaging method.Secondly,FGG-NUFFT and reverse FGG-NUFFT are used to replace the interpolation and Fourier transform in MF-based imaging methods,and a sensing matrix with high precision and high efficiency is constructed according to the traditional imaging process.Thirdly,a fast imaging recovery is performed by using the improved separable surrogate functionals(SSF)optimization algorithm,only with matrix and vector multiplication.Finally,a 3 D imagery of the near-field target is obtained by using both the horizontal and the pitching interferometric phase information.This paper contains two imaging models,the only difference is the sub-aperture method used in inverse synthetic aperture radar(ISAR)imaging.Compared to traditional CS-based imaging methods,the proposed method includes both forward transform and inverse transform in each iteration,which improves the quality of reconstruction.The experimental results show that,the proposed method improves the imaging accuracy by about O(10),accelerates the imaging speed by five times and reduces the memory usage by about O(10~2).

An improved bicubic imaging fitting algorithm for 3D radar detection target

3D ground-penetrating radar has been widely used in urban road underground disease detection due to its nondestructive,efficient,and intuitive results.However,the 3D imaging of the underground target body presents the edge plate phenomenon due to the space between the 3D radar array antennas.Consequently,direct 3D imaging using detection results cannot reflect underground spatial distribution characteristics.Due to the wide-beam polarization of the ground-penetrating radar antenna,the emission of electromagnetic waves with a specific width decreases the strong middle energy on both sides gradually.Therefore,a bicubic high-precision 3D target body slice-imaging fitting algorithm with changing trend characteristics is constructed by combining the subsurface target characteristics with the changing spatial morphology trends.Using the wide-angle polarization antenna’s characteristics in the algorithm to build the trend factor between the measurement lines,the target body change trend and the edge detail portrayal achieve a 3D ground-penetrating radar-detection target high-precision fitting.Compared with other traditional fitting techniques,the fitting error is small.This paper conducts experiments and analyses on GpaMax 3D forward modeling and 3D ground-penetrating measured radar data.The experiments show that the improved bicubic fitting algorithm can eff ectively improve the accuracy of underground target slice imaging and the 3D ground-penetrating radar’s anomaly interpretation.

A New Three-Dimensional(3D)Printing Prepress Algorithm for Simulation of Planned Surgery for Congenital Heart Disease

Background:Three-dimensional printing technology may become a key factor in transforming clinical practice and in significant improvement of treatment outcomes.The introduction of this technique into pediatric cardiac surgery will allow us to study features of the anatomy and spatial relations of a defect and to simulate the optimal surgical repair on a printed model in every individual case.Methods:We performed the prospective cohort study which included 29 children with congenital heart defects.The hearts and the great vessels were modeled and printed out.Measurements of the same cardiac areas were taken in the same planes and points at multislice computed tomography images(group 1)and on printed 3D models of the hearts(group 2).Pre-printing treatment of the multislice computed tomography data and 3D model preparation were performed according to a newly developed algorithm.Results:The measurements taken on the 3D-printed cardiac models and the tomographic images did not differ significantly,which allowed us to conclude that the models were highly accurate and informative.The new algorithm greatly simplifies and speeds up the preparation of a 3D model for printing,while maintaining high accuracy and level of detail.Conclusions:The 3D-printed models provide an accurate preoperative assessment of the anatomy of a defect in each case.The new algorithm has several important advantages over other available programs.They enable the development of customized preliminary plans for surgical repair of each specific complex congenital heart disease,predict possible issues,determine the optimal surgical tactics,and significantly improve surgical outcomes.

A modified OMP method for multi-orbit three dimensional ISAR imaging of the space target

The conventional two dimensional(2D)inverse synthetic aperture radar(ISAR)imaging fails to provide the targets'three dimensional(3D)information.In this paper,a 3D ISAR imaging method for the space target is proposed based on mutliorbit observation data and an improved orthogonal matching pursuit(OMP)algorithm.Firstly,the 3D scattered field data is converted into a set of 2D matrix by stacking slices of the 3D data along the elevation direction dimension.Then,an improved OMP algorithm is applied to recover the space target's amplitude information via the 2D matrix data.Finally,scattering centers can be reconstructed with specific three dimensional locations.Numerical simulations are provided to demonstrate the effectiveness and superiority of the proposed 3D imaging method.

Research on a bifurcation location algorithm of a drainage tube based on 3D medical images

Based on patient computerized tomography data,we segmented a region containing an intracranial hematoma using the threshold method and reconstructed the 3D hematoma model.To improve the efficiency and accuracy of identifying puncture points,a point-cloud search arithmetic method for modified adaptive weighted particle swarm optimization is proposed and used for optimal external axis extraction.According to the characteristics of the multitube drainage tube and the clinical needs of puncture for intracranial hematoma removal,the proposed algorithm can provide an optimal route for a drainage tube for the hematoma,the precise position of the puncture point,and preoperative planning information,which have considerable instructional significance for clinicians.

Deep-Learning-Empowered 3D Reconstruction for Dehazed Images in IoT-Enhanced Smart Cities

With increasingly more smart cameras deployed in infrastructure and commercial buildings,3D reconstruction can quickly obtain cities’information and improve the efficiency of government services.Images collected in outdoor hazy environments are prone to color distortion and low contrast;thus,the desired visual effect cannot be achieved and the difficulty of target detection is increased.Artificial intelligence(AI)solutions provide great help for dehazy images,which can automatically identify patterns or monitor the environment.Therefore,we propose a 3D reconstruction method of dehazed images for smart cities based on deep learning.First,we propose a fine transmission image deep convolutional regression network(FT-DCRN)dehazing algorithm that uses fine transmission image and atmospheric light value to compute dehazed image.The DCRN is used to obtain the coarse transmission image,which can not only expand the receptive field of the network but also retain the features to maintain the nonlinearity of the overall network.The fine transmission image is obtained by refining the coarse transmission image using a guided filter.The atmospheric light value is estimated according to the position and brightness of the pixels in the original hazy image.Second,we use the dehazed images generated by the FT-DCRN dehazing algorithm for 3D reconstruction.An advanced relaxed iterative fine matching based on the structure from motion(ARI-SFM)algorithm is proposed.The ARISFM algorithm,which obtains the fine matching corner pairs and reduces the number of iterations,establishes an accurate one-to-one matching corner relationship.The experimental results show that our FT-DCRN dehazing algorithm improves the accuracy compared to other representative algorithms.In addition,the ARI-SFM algorithm guarantees the precision and improves the efficiency.

Super-resolution amplification of bitmap images based on 3D modeling theory

As a general format of the image,bitmap(BMP)image has wide applications,and consequently it is an important part of image processing.By segmenting the bitmap and combining the three-dimesional(3D)model of the discrete algorithm with the scanning line compensation algorithm,a mathematical model is built.According to the topological relations between several control points on the model surface,the surface of the model is discretized,and a planar triangle sequence is used to describe 3D objects.Finally,the bitmap is enlarged by combining the borrowing compensation based on 3D modeling principle of discrete algorithm with the scanning line compensation algorithm of binary lattice image,thus getting a relatively clear enlarged BMP image.

基于改进3D SPIHT的MRI序列图像压缩方法

目的研究一种有效的MRI序列图像压缩方法。方法以2组不同数量、不同层厚的MRI序列图像为例,针对3D SPIHT算法运算复杂度,在对D型、L型表项重复判断的不足上,提出了一种改进的3DSPIHT方法;同时,根据MRI序列图像的相关性特点,提出了分组编/解码的方法,结合3D小波变换和应用改进的3D SPIHT方法,实现了MRI序列图像压缩。结果分组结合改进3D SPIHT方法与2DSPIHT,3D SPIHT相比,能够得到较好重构图像,同时,峰值信噪比(PSNR)提高了1～8 dB左右。结论在相同码率下,分组结合改进3D SPIHT的方法提高了PSNR和图像恢复质量,可以更好地解决大量MRI序列图像存储与传输问题。

DLT算法中象平面误差对三维重构的影响

DLT算法是利用平面图象进行三维重构的广泛采用的基本算法。本文针对平面图象处理中难以避免的象坐标误差 ,讨论了各坐标误差对三维重构坐标的影响 ,由此分析了三维重构坐标对各象坐标误差的敏感程度 ,并进行了数值模拟实验。结果表明三维重构的各分坐标对象坐标误差具有不同的敏感度 ,而且与相机的空间位置有密切的联系。这说明DLT算法中虽然在理论上对相机的空间配置无特别要求 。

AGI-T3在输水隧洞超前地质预报中的应用

针对传统超前地质预报设备造价昂贵、占用施工时间长,数据处理复杂等问题,研究一种高效经济的新型地质预报成像系统AGI-T3,将AGI-T3与TSP203plus用于千岛湖配水工程石毛畈主洞岩体完整性探测,阐述了AGI-T3观测系统布设方式、数据处理流程及与TSP203plus的差异,分析了AGI-T3原始数据特性及岩体破碎区对应的AGI-T3异常特征。结果表明:AGI-T3采用绕射扫描叠加与共反射面元叠加(CRS)相结合的偏移技术进行三维成像,从而避免了动静校正带来的误差。AGI-T3采用F-K滤波与负速度对比扫描相结合的方法拾取反射层,一定程度上提高了三维成像的精度。隧洞实际开挖表明,两种地震反射技术均能较好的反映掌子面前方岩体完整性变化特征,破碎岩体对应AGI-T3异常纵波波速偏低、反射层密集或存在强负反射层面,在TSP成果中表现为波速、密度及静态杨氏模量呈现极小值。AGI-T3探测分辨率较TSP203plus偏低,波速曲线与偏移成果局部一致性较差,但其有效预报范围内对波阻抗显著变化的界面探测灵敏度较高,且地震波激发方式多样化。研究成果作为一种便捷型中长距离预报系统有一定的推广价值。

Three-Dimensional Modeling of the Retinal Vascular Tree via Fractal Interpolation

In recent years,the three dimensional reconstruction of vascular structures in the field of medical research has been extensively developed.Several studies describe the various numerical methods to numerical modeling of vascular structures in near-reality.However,the current approaches remain too expensive in terms of storage capacity.Therefore,it is necessary to find the right balance between the relevance of information and storage space.This article adopts two sets of human retinal blood vessel data in 3D to proceed with data reduction in the first part and then via 3D fractal reconstruction,recreate them in a second part.The results show that the reduction rate obtained is between 66%and 95%as a function of the tolerance rate.Depending on the number of iterations used,the 3D blood vessel model is successful at reconstruction with an average error of 0.19 to 5.73 percent between the original picture and the reconstructed image.

New Algorithm for 3D Facial Model Reconstruction and Its Application in Virtual Reality

3D human face model reconstruction is essential to the generation of facial animations that is widely used in the field of virtual reality (VR). The main issues of 3D facial model reconstruction based on images by vision technologies are in twofold: one is to select and match the corresponding features of face from two images with minimal interaction and the other is to generate the realistic-looking human face model. In this paper, a new algorithm for realistic-looking face reconstruction is presented based on stereo vision. Firstly, a pattern is printed and attached to a planar surface for camera calibration, and corners generation and corners matching between two images are performed by integrating modified image pyramid Lucas-Kanade (PLK) algorithm and local adjustment algorithm, and then 3D coordinates of corners are obtained by 3D reconstruction. Individual face model is generated by the deformation of general 3D model and interpolation of the features. Finally, realistic-looking human face model is obtained after texture mapping and eyes modeling. In addition, some application examples in the field of VR are given. Experimental result shows that the proposed algorithm is robust and the 3D model is photo-realistic.

三维直方图重建和降维的Otsu阈值分割算法

针对三维Otsu阈值分割算法中因区域误分而产生的抗噪性差这一问题,提出了一种三维直方图重建和降维的Otsu阈值分割算法.该方法首先在详细分析三维直方图中噪声点分布的基础上,通过重建三维直方图,减弱了噪声干扰;然后将三维直方图区域划分由八分法改为二分法,使得阈值搜索的空间维度从三维降低到一维,减少了处理时间和存储空间.本文最后给出了算法的分割结果和运行时间,并与三维Otsu方法、二维分解法和二维斜分法进行对比.实验结果表明,本文算法的抗噪性更强,且分割效果更为理想,同时时间复杂度也远低于三维Otsu法.

探地雷达近场三维距离偏移成像算法

在距离偏移算法基础上提出了近场条件下的探地雷达三维成像方法,同时对后向投影钟法进行了讨论.理论分析表明:近场三维距离偏移算法与后向投影算法相比,能在较大程度上减少运算量.利用试验数据对两种算法分别做了成像研究,验证了近场三维距离偏移箅法的正确性及其实时处理能力.

基于星载毫米波顺轨-交轨InISAR的空间运动目标三维成像技术研究

研究了低信噪比情况下的星载毫米波顺轨/交轨In-ISAR空间目标三维成像问题。由于传统的RD成像算法在目标尺寸较大和分辨率要求较高时不能取得较好的成像效果,故将波数域成像算法引入运动目标成像处理以获得高分辨率的二维图像,继而将顺轨/交轨三天线ISAR图像分别进行干涉处理,获得了目标上各散射点的三维位置。作为二维成像、图像配准等重要环节的基础参数,对低信噪比下的目标检测和三维运动参数估计进行了研究,分析了速度估计精度要求。最后,仿真结果表明了顺轨/交轨In-ISAR系统的有效性。

基于等价三维熵与鲸鱼优化算法的图像分割研究

为提高三维最大熵法对图像分割的时效性,提出一种基于等价三维熵与鲸鱼优化算法(WOA)的图像分割方法。设计一种不含对数运算的等价三维熵法,基于WOA算法求解最佳阈值,以避免穷举搜索并提高算法效率。实验结果表明,相比传统三维最大熵法、等价三维最大熵法,该方法在不影响分割效果的前提下,能够减少运行时间,且在抗噪性和保留图像细节方面具有明显优势。

采用RELAX算法提高单脉冲三维成像横向分辨率

根据宽带比相单脉冲三维成像雷达测量目标散射点横向位置原理,分析仿真了散射点间相互干扰对目标散射点横向位置测量的影响。应用RELAX算法直接估计去斜率后正弦信号的幅度和频率参数,提高散射点横向位置测量精度。通过分析及仿真可知,RELAX算法的引入使横向位置测量精度有了较明显改善。

油气管道漏磁检测缺陷的三维成像技术

漏磁检测是油气管道常用的无损检测方法,检测的重点是根据测量的漏磁信号重构缺陷的轮廓。提出了基于小波神经网络的三维成像方法,利用图像函数矩阵表达出管道缺陷的三维图像,矩阵元素值对应着缺陷的深度。利用小波神经网络,建立了由缺陷漏磁信号到图像函数矩阵关系的映射。选用的小波函数是墨西哥草帽小波,采用随机梯度下降算法训练。训练样本为三维有限元仿真数据和测量数据。采用训练数据对小波神经网络进行逼近缺陷图像函数矩阵的训练,然后用训练好的小波神经网反演给定数据,重构缺陷图像。实验结果表明,该方法能够实现三维缺陷漏磁检测的成像化及可视化。

面向体三维显示器的图形算法设计

针对一种基于旋转双螺旋屏幕逐层扫描技术的体三维显示系统,设计并实现了一套支持真实空间三维显示的图形算法体系。算法核心主要包括立体图元的体素化,切片图像渲染和投影同步控制等3个环节。图形系统通过离散三维网格模型获取体三维显示需要的体数据,并根据螺旋屏幕的几何特征将物体的体数据集渲染成切片图像序列发送至高速投影单元,在保持投影与屏幕旋转同步的情况下,快速变换的投影图像基于视觉暂留融合成具有真实物理深度的三维影像。算法在体三维显示器样机上进行了验证,显示的三维影像占据真实物理空间,具备全方向观察角度,围绕显示器可直接观察到立体图像各个不同侧面,如同观察真实物体一样。

基于OpenCL的三维可视化加速模型

由多张相关的二维图像构建成在屏幕上显示的三维立体图像的三维可视化技术对医学诊断具有重要意义,但若绘制时间过长将限制该技术在实践中的应用,研究既能满足医生临床诊断需要,又能快速实现三维可视化的加速模型具有实用价值.提出的基于Open CL的三维可视化加速模型是一种基于Open CL架构,通过合理设计内核函数实现改进的光线投射算法在GPU上并行和并发运行的三维可视化加速模型,该模型实现代码可不用修改在两大主流显卡平台NVIDIA和AM D上任意移植,实验证明,该模型绘制三维图像速度与NVIDIA的CUDA实现模型相当,快于传统GPU模型,但其图像渲染更逼真和清晰,实现代码具有显卡平台移植性.