基于优化估计的深度图像修复与误差补偿方法研究

针对Kinect传感器在获取深度图像时存在深度值随机跳变的不准确性问题,基于最优估计的思想,提出卡尔曼滤波与多帧平均法相结合的图像修复方法。首先利用卡尔曼滤波对多幅深度图像进行修复处理,实现Kinect传感器在采集信息过程中随着时间递推,深度值的跳变逐渐趋于平稳的效果;然后基于多幅图像平均法确定最终的深度图像,解决了Kinect获取深度值存在误差导致的不精确问题。实验结果表明,该算法的均方根误差为38.102 5,平均梯度为0.471 3,信息熵为6.191 8,与单幅图像修复效果相比,得到的深度图像边缘更加清晰。     

基于梯度的数字体图像相关方法测量物体内部变形

数字体图像相关方法通过分析两幅以体素为单位的三维体图像获得物体内部的三维变形信息.在利用数字体图像相关方法测量物体内部变形的过程中,整体素的位移场可以通过简单的空域搜索获得,因此如何计算亚体素位移是提高该方法位移测量精度的关键.介绍了一种基于空间灰度梯度的亚体素位移测量算法,并用计算机模拟生成的可精确控制位移的三维散斑...     

宽场光学相干断层成像系统的三维显微成像

宽场相干断层成像技术（WFOCT）具有提高OCT系统的扫描速率和实现高分辨率的三维显微技术等优点,成为当前研究的热点。本文阐述了WFOCT的基本原理,利用八步移相法重建出玻璃物体微细结构的断层图像,研究了宽场OCT系统对玻璃材料的纵向分辨率和探测深度,其中探测深度可达3.3 mm。在获得多幅断层图像的基础上,利用VC6.0和OpenGL混合编程,采用移动立方体（MC）算法重建出玻璃物体微细结构的三维图像。实验结果表明,WFOCT系统不但能够在生物组织检测等医学方面得到应用,而且对反射率较高的物体能够完成三维形貌显微成像探测和深度探测。     

基于光场深度序列的大视野图像拼接算法

针对现有光场深度重建算法只能获取单一视角深度信息,三维建模应用受限的问题,提出一种大视野图像拼接算法。该算法基于三维光场重建的深度图像序列,采用双边滤波及插值算法对图像进行去除噪声,利用基于边缘曲率极值的角点检测算法,并通过最小曲率偏差的列间度量匹配实现了图像之间的精确配准,采用改进的加权平均方法对重叠区域进行融合操作,既保留图像细节又拓展图像视野。实验结果表明,该算法能够有效实现光场深度图像序列的平滑拼接,有利于形成大视野深度数据,为大场景的三维重建奠定了基础。     

针对小动物的锥束CT重建的研究及验证

基于经典3D Shepp-Logan模型,应用射线追踪和射线衰减定律得到锥束CT的模拟仿真数据.利用FDK三维重建算法实现锥束CT图像重建,采用仿真图像对重建算法进行了验证,通过搭建的锥束CT系统和自制仿体进行了层析成像和图像重建.结果表明:算法可较为准确地重建出原物体的空间分布和密度关系,针对仿真数据的中心断层重建图像的空间分辨率可达到8 lp/mm.     

基于体感控制耦合深度相机的手势识别算法

针对当前手势识别算法易受光线变化、复杂场景等干扰,从而导致手势识别准确性下降的问题,定义了一种体感控制与深度相机的手势识别算法。所提出的手势识别方法结合了体感控制(Leap Motion)传感器和Kinect深度传感器,可以有效提高手势识别精度与鲁棒性。通过体感控制传感器提取指尖与手的质心距离、指尖与手掌平面的高度、指尖与手掌中心的角度,以及指尖在手参照系统中的3D位置;通过Kinect深度传感器来提取手指样本与手部中心的距离、手部轮廓的局部曲率、手部形状的连通区域以及距离特征之间的相似性;为了结合两种不同传感器数据的互补信息,摒弃冗余,通过采集的指尖3D位置,找到旋转平移参数,以最小化所有采集帧中指尖点的平均投影误差来定义一种联合校准方法,确定体感控制传感器和Kinect深度传感器的外部参数,完成两种传感器坐标转换;采用支持向量机(SVM)进行分类学习,完成手势识别任务。实验表明：相对于已有的手势识别算法,所提算法不仅在Jochen.Triesch手势数据库中具有更高的平均识别率,约为97%,而且在不同光线、不同肤色和背景的复杂环境下,其同样具有更高的准确率与稳健性。     

针对小动物的锥束CT重建的研究及验证

基于经典3D Shepp-Logan模型,应用射线追踪和射线衰减定律得到锥束CT的模拟仿真数据.利用FDK三维重建算法实现锥束CT图像重建,采用仿真图像对重建算法进行了验证,通过搭建的锥束CT系统和自制仿体进行了层析成像和图像重建.结果表明:算法可较为准确地重建出原物体的空间分布和密度关系,针对仿真数据的中心断层重建图像的空间分辨率可达到8lp/mm.     

对复杂自由曲面的纹理重建方法

提出一种基于马尔科夫优化策略复杂自由曲面的纹理重建方法,该方法利用实验室研制的三维数字化设备对目标物体的深度数据和纹理数据进行采集,将局部采集的深度像数据匹配到全局坐标系下,建立物体的几何模型;然后通过坐标变换,把采集的纹理照片映射到重建的几何模型表面,并进行曲面纹理融合处理,实现自由曲面的纹理重建.该方法对物体的形貌没要求,能实现结构复杂的自由曲面的纹理重建,得到高保真质量的真实感模型.采用该算法对几种不同的实物进行数据采集和真实感三维重建,实验结果验证了算法的可靠性和有效性.     

基于衍射追迹的集成成像重构算法

衍射受限集成成像光线追迹算法所重构的深度平面是物体深度的重聚焦图像,重构图像像质模糊,不利于物体的三维重构。针对这些问题,提出了一种基于衍射追迹的深度平面重构算法,由菲涅耳衍射公式计算物空间点源传播至成像系统各平面的光场分布,最终求得每个采样点在传感器上的光强脉冲响应,通过反解与光强脉冲响应相关的线性方程组,实现物体深度平面的图像重构。仿真结果表明,采用该方法实现的重构图像是物体的深度平面切片,而且图像像质接近于原始图像,有利于物体的三维重建。     

一种散乱点云的均匀精简算法

针对散乱点云数据密度大、重建时间长、效率低等问题,提出了一种散乱点云的均匀精简算法。该算法基于开源C++编程库点云库(PCL),利用PCL的体素化栅格类创建一个K邻域三维体素栅格,结合包围盒法对输入的点云数据进行K邻域距离计算和法线估计,确定每个小立方栅格的重心,并以其来近似显示这个小立方栅格内所有的数据点,达到精简点云的目的,最后利用贪婪三角投影类对精简后的点云实现三角网格面重建并显示其效果。实验结果表明,该算法在充分保留点云数据几何特征的前提下,能有效滤除部分点云数据冗余量,且精简结果比较均匀,避免了大规模精简所出现的空白区域,提高了重建效率。     

An improved edge detection algorithm for depth map inpainting

Three-dimensional (3D) measurement technology has been widely used in many scientific and engineering areas. The emergence of Kinect sensor makes 3D measurement much easier. However the depth map captured by Kinect sensor has some invalid regions, especially at object boundaries. These missing regions should be filled firstly. This paper proposes a depth-assisted edge detection algorithm and improves existing depth map inpainting algorithm using extracted edges. In the proposed algorithm, both color image and raw depth data are used to extract initial edges. Then the edges are optimized and are utilized to assist depth map inpainting. Comparative experiments demonstrate that the proposed edge detection algorithm can extract object boundaries and inhibit non-boundary edges caused by textures on object surfaces. The proposed depth inpainting algorithm can predict missing depth values successfully and has better performance than existing algorithm around object boundaries.     

Fusion of 3D laser scanner and depth images for obstacle recognition in mobile applications

The problem of obstacle detection and recognition or, generally, scene mapping is one of the most investigated problems in computer vision, especially in mobile applications. In this paper a fused optical system using depth information with color images gathered from the Microsoft Kinect sensor and 3D laser range scanner data is proposed for obstacle detection and ground estimation in real-time mobile systems. The algorithm consists of feature extraction in the laser range images, processing of the depth information from the Kinect sensor, fusion of the sensor information, and classification of the data into two separate categories: road and obstacle. Exemplary results are presented and it is shown that fusion of information gathered from different sources increases the effectiveness of the obstacle detection in different scenarios, and it can be used successfully for road surface mapping.     

X射线光场成像技术研究

X射线三维成像技术是目前国内外X射线成像研究领域的一个研究热点.但针对一些特殊成像目标,传统X射线计算层析(CT)成像模式易出现投影信息缺失等问题,影响CT重建的图像质量,使得CT成像的应用受到一定的限制.本文主要研究了基于光场成像理论的X射线三维立体成像技术.首先从同步辐射光源模型出发,对X射线光场成像进行建模;然后,基于光场成像数字重聚焦理论,对成像目标场在深度方向上进行切片重建.结果表明:该方法可以实现对成像目标任一视角下任一深度的内部切片重建,但是由于光学聚焦过程中的离焦现象,会引入较为严重的背景噪声.当对其原始数据进行滤波后,再进行X射线光场重聚焦,可以有效消除重建伪影,提高图像的重建质量.本研究既有算法理论意义,又可应用于工业、医疗等较复杂目标的快速检测,具有较大的应用价值.     

融合Kinect与γ相机图像的放射性区域重建与定位

针对核设施退役、核应急处置过程中放射性分布信息的可视化需求,提出了一种基于Kinect与γ相机图像信息融合的放射性区域重建与定位方法。首先,基于γ相机的特殊成像方式,构建了Kinect与γ相机组合成像模型,并完成相机组合联合标定;其次,基于视觉地图构建方法,建立了核辐射环境稠密点云地图并得到Kinect位姿;然后,提取γ相机图像中的放射性分布信息,根据相机组合模型计算地图中的放射性区域点云;最后,基于最小包围盒对γ相机成像的中心区域进行三维定位。在实验中,通过将Kinect和γ相机数据同步与空间对齐,在少量γ相机图像的情况下,实现了单个点源的三维分布重建模型与辐射场景地图的融合。在8×12 m2的实验室环境中点源定位的均方根误差为0.11 m,证明了本文方法的有效性。     

Three-dimensional integral imaging with improved visualization using subpixel optical ray sensing

In this Letter, we propose an improved three-dimensional (3D) image reconstruction method for integral imaging. We use subpixel sensing of the optical rays of the 3D scene projected onto the image sensor. When reconstructing the 3D image, we use a calculated minimum subpixel distance for each sensor pixel instead of the average pixel value of integrated pixels from elemental images. The minimum subpixel distance is defined by measuring the distance between the center of the sensor pixel and the physical position of the imaging lens point spread function onto the sensor, which is projected from each reconstruction point for all elemental images. To show the usefulness of the proposed method, preliminary 3D imaging experiments are presented. Experimental results reveal that the proposed method may improve 3D imaging visualization because of the superior sensing and reconstruction of optical ray direction and intensity information for 3D objects.     

Depth-controlled reconstruction of 3D integral image using synthesized intermediate sub-images

In this paper, we propose a method that controls the depth of the three-dimensional (3D) object existing over the depth-of-focus in integral imaging. The depth control method is performed only in a computer by synthesizing the intermediate sub-images between original sub-images obtained by transforming the captured elemental images. In the reconstruction process, we can obtain reconstructed 3D images with the better image quality within depth-of-focus than that reconstructed over the depth-of-focus. To demonstrate the feasibility of our method, optical and computational experiments are carried out and its results are presented.     

一种三维物体相息图的迭代计算方法

在传统迭代傅里叶变换算法的基础上,提出了一种计算三维物体相息图的新方法.基于层析法将三维物体的多个分层物面作为衍射再现图像,在一个输入面(相息图)和多个输出面(再现像)之间进行迭代.通过在傅里叶迭代运算中引入距离相位因子,表示物体不同物面的深度,体现了物体的三维特征.实验结果证明了本文算法良好的收敛特性和再现性能.最后,分析了物面数量和间距对全息再现质量的影响,利用液晶空间光调制器采用时分复用的方法还原了三维物体的多个物面.     

Three-dimensional free view reconstruction in axially distributed image sensing

In this Letter, we propose a three-dimensional(3D) free view reconstruction technique in axially distributed image sensing(ADS). In typical integral imaging, free view reconstructed images can be obtained by tilting all elemental images or tilting the reconstruction plane due to large lateral perspectives for 3D objects. In conventional ADS, the reconstructed images at only a front view can be generated since the sensor is moved along with its optical axis so that it has small lateral perspectives for 3D objects. However, the reconstructed 3D images at any viewing point may be obtained because the virtual viewing camera may capture these slightly different perspectives for 3D objects. Therefore, in this Letter, we employ the virtual viewing camera to visualize the 3D images at the arbitrary viewing point. To support our proposed method, we show the experimental results.     

Optical display of true 3D objects in depth-priority integral imaging using an active sensor

In this paper, we propose a system combining the pickup process using an active sensor and the display process using depth-priority integral imaging (DPII) system to display true three-dimensional (3D) objects within large depth through real and virtual image fields. The active sensor provides depth map and color images of 3D objects. Using captured depth map and original color images, elemental images are computationally synthesized and displayed optically in DPII system. Proposed system provides scaling of 3D scenes for true 3D object. To show the usefulness of proposed system, we carry out the experiment for true 3D objects of three character patterns and present the experimental results.