GPU多重纹理加速三维CT图像重建

三维锥束CT图像重建运算量大,纯软件（仅使用CPU）计算时间较长。为了充分利用计算机图形处理器（Graphic Process Unit,GPU）的并行处理能力以及提高数据传输效率,研究了一种结合使用GPU多重纹理（multitexture）加速三维锥束CT的FDK图像重建过程的方法。该方法采用多重纹理映射来提高反投影速度、减少中间数据存储量、减少浮点累加次数,使用顶点颜色通道来实现距离加权运算,采用扩展方法来增加并行反投影的纹理单元,从而提高重建速度。计算机实验结果表明,使用普通PC机重建尺寸为2563的图像,在保证数据精度为16 bit浮点数的要求下,GPU反投影计算可以在10 s以内完成。与仅使用CPU的重建方法相比,GPU重建图像加速方法达到了较高的时间加速比。     

基于CUDA的图形处理器加速锥束CT重建算法的研究

锥束CT图像重建数据量巨大、运算复杂度高,重建时间长,难以满足实际应用的需求。研究基于CUDA的图形处理器加速锥束CT重建算法的方案,通过有效的并行策略来提高滤波和反投影过程的时间,并利用常数存储器和纹理存储器来提高数据访存效率。实验证明在保证重建质量的情况下,重建速度可以提高82倍。     

扇束CT极坐标反投影重建算法的对称优化

为了提高扇束滤波反投影(FBP)算法重建图像的速度,提出一种极坐标反投影算法的优化快速重建方法。算法利用三角函数对称性对多幅预处理后的投影数据同时进行极坐标反投影运算;在反投影数据坐标转换时运用像素位置参数的对称性,以减少双线性插值的计算量。实验结果表明,在不牺牲重建图像质量前提下,与传统卷积反投影重建算法相比,优化算法的重建速度提高8倍以上。该优化方法也适应于三维锥束重建,并可推广到多层螺旋三维重建。     

BPF 重建算法的 CUDA 并行实现

反投影滤波(Backprojection-Filter,BPF)算法凭借其可实现感兴趣区域重建的优点,近年来逐渐被应用到锥束CT中。但是,由于算法的复杂性,实践中存在耗时问题,同时其GPU加速的实现亦存在显存不足等问题。因此,文章提出了一种基于CUDA的BPF并行加速算法。通过设计高效的算法框架,在保留其重建精度的前提下,有效地减少所需显存。此外,总结了正投影算法及BPF算法中采用的加速策略,如利用算法特征加速等,并引入显存池的概念优化算法架构。仿真实验结果表明,在精确重建的前提下,采用新框架重建512×512×512数据只需8.055 s,感兴趣区域重建只需4.566 s,只需1.523 s便可输出第一部分数据,且能把显存占用从2.5 GB减少到100 MB以下,适用于大数据重建。     

锥束CT的FDK算法与CUDA实现

计算机层析成像技术,在医学和工业等诸多领域中有着广泛应用。在三维锥束CT图像重建算法中,基于圆形轨道和二维平板探测器的FDK算法最为著名。传统CPU上实现的FDK算法,计算复杂性主要集中在所谓的反投影阶段,占据了整个重建时间的99%。给出了基于CUDA统一计算架构的FDK算法的GPU实现,对于整个重建过程获得了超过百倍的加速。     

锥束CT检测成像仿真系统的研究与实现

设计并实现一个用于CT专业教学和科研的锥束CT检测成像仿真系统.该仿真系统能够模拟对CT设备的控制,生成正投影数据,重建被测物体,并能对重建结果进行三维显示.该系统包括如下关键技术:按真实比例对CT设备建模,实现了锥束CT工作过程的可视化;用场景图方法组织CT场景,简化了场景图形的管理方式;采用GPU加速CT正投影、图像重建和体绘制算法,在一定程度上解决了锥束CT大数据量快速计算问题.实验结果表明,该系统具有较快的运行速度,可满足用户交互操作的需要.     

基于二叉树和GPU的无缝地形场景渲染方法

设计了一种基于图形处理器(GPU)的无缝地形渲染方法。该方法基于二叉树构建多层次地形网格,该网格用基于行、列号的地形模板表示。在设计过程中,将高程数据转化为适于GPU读取的高程纹理图,再通过顶点纹理提取(VTF)技术从纹理图中采样出高程值用于渲染,整个过程在GPU端完成,提升了地形数据访问效率。同时,采用实时优化自适应网格(ROAM)算法的强制拆分法,通过控制相邻地形块的等级来消除裂缝。最后,采用TriangleStrip方式进行渲染,避免了相邻三角形中顶点坐标数据的重复传递,减少了传递到GPU的数据量。用两块地形数据对算法渲染效率进行了检验,并将算法与Clipmap算法进行了帧率对比。结果表明,该算法有效解决了分块数据的裂缝问题,达到了交互式地形渲染的要求。     

基于GPU加速的锥束CT重建算法研究

锥束计算机断层扫描（Cone-Beam Computed Tomography，CBCT）具有采集速度快和空间分辨率高等特点，被生物医学等领域广泛关注。然而通过CPU串行处理CBCT重建中海量投影数据非常耗时，难以满足实时性的需求。GPU的发展为CBCT重建的并行加速提供了条件。根据三角函数周期性的特点对FDK算法进行了改进，并利用GPU实现了12幅投影数据同时并行计算。实验结果表明，相比于传统基于CPU的重建算法，基于GPU的CBCT重建算法在保证图像质量的前提下，将重建速度提高了超过310倍。     

基于GPU的海量离散点高程并行插值算法

提出一种基于GPU的高程并行插值算法,实现了对三维地表上海量离散点的并行加速渲染。通过高程纹理组织三维地表网格高程数据作为离散点渲染的基础,并通过GLSL编写GPU着色器程序动态控制图形渲染管线,实现视点相关的高程并行插值算法。实验结果表明,提出的基于GPU的高程并行插值算法较传统的内存插值算法,将三维地表上海量离散点的渲染量级从百万级提高到了千万级。     

多通道快速GPU光线投射算法

现有基于GPU加速的光线投射算法为满足实时交互的需求,通常在用户交互过程中,采用降低采样频率的方法来提高重建速度,却丢失了三维数据场的信息,极大降低了重建图像的质量.针对这一问题,在分析GPU渲染管道线和图像插值重建技术的基础上,提出多通道快速GPU光线投射算法.利用离屏渲染技术,设置比显示分辨率低4～16倍的渲染分辨率,在此渲染分辨率下进行正常采样的光线投射算法,将渲染分辨率下重建结果重新作为输入,进行高分辨率重建,并显示结果.实验结果表明,该方法可以在满足重建图像质量的前提下,有效提高重建速度.     

Shape from texture using local spectral moments

Presents a non-feature-based solution to the problem of computing the shape of curved surfaces from texture information. First, the use of local spatial-frequency spectra and their moments to describe texture is discussed and motivated. A new, more accurate method for measuring the local spatial-frequency moments of an image texture using Gabor elementary functions and their derivatives is presented. Also described is a technique for separating shading from texture information, which makes the shape-from-texture algorithm robust to the shading effects found in real imagery. Second, a detailed model for the projection of local spectra and spectral moments of any surface reflectance patterns (not just textures) is developed. Third, the conditions under which the projection model can be solved for the orientation of the surface at each point are explored. Unlike earlier non-feature-based, curved surface shape-from-texture approaches, the assumption that the surface texture is isotropic is not required; surface texture homogeneity can be assumed instead. The algorithm's ability to operate on anisotropic and nondeterministic textures, and on both smooth- and rough-textured surfaces, is demonstrated     

Projection Mapping on Arbitrary Cubic Cell Complexes

This work presents a new representation used as a rendering primitive of surfaces. Our representation is defined by an arbitrary cubic cell complex: a projection‐based parameterization domain for surfaces where geometry and appearance information are stored as tile textures. This representation is used by our ray casting rendering algorithm called projection mapping, which can be used for rendering geometry and appearance details of surfaces from arbitrary viewpoints. The projection mapping algorithm uses a fragment shader based on linear and binary searches of the relief mapping algorithm. Instead of traditionally rendering the surface, only front faces of our rendering primitive (our arbitrary cubic cell complex) are drawn, and geometry and appearance details of the surface are rendered back by using projection mapping. Alternatively, another method is proposed for mapping appearance information on complex surfaces using our arbitrary cubic cell complexes. In this case, instead of reconstructing the geometry as in projection mapping, the original mesh of a surface is directly passed to the rendering algorithm. This algorithm is applied in the texture mapping of cultural heritage sculptures.     

Animating static objects by illusion‐based projection mapping

By applying scientific knowledge about human visual processing, we have recently developed a light projection technique, called Deformation Lamps, which can add a variety of illusory, yet realistic distortions, to a wide range of static projection targets. In this paper, to explain how Deformation Lamps works, we first describe its basic algorithm and related human visual processing. We then describe the latest version of the Deformation Lamps system. It is a ready‐to‐use application that automatically finds projection targets and projects motion‐inducer patterns in alignment with images or textures on the targets' surfaces. The application also supports interactive editing of animation contents.     

基于面法向的快速纹理合成

根据模型上各相邻三角面的法向,采用广度优先策略将模型划分。在划分中采用正向投影映射将各模型块参数化并对其进行评价,对于具有较大扭曲的模型块,将其再次细分直到扭曲值满足给定的阀值。对于各模型块的接缝采用Alpha-Blend技术将纹理拼接成一个连续的整体。该算法适用于任意曲面和多种纹理。     

Multiresolution Visualization of Higher Order Adaptive Finite Element Simulations

h –p–adaptive projection with respect to any prescribed threshold value for the visual error. This projection can then be processed by various local rendering methods, e.g. color coding of data or isosurface extraction. Especially for color coding purposes modern texture capabilities are used to directly render higher polynomial data by superposition of polynomial basis function textures and final color look-up tables. Numerical experiments from CFD clearly demonstrate the applicability and efficiency of our approach. Received September 25, 2001; revised March 31, 2003 Published online: May 26, 2003 The authors acknowledge the valuable hints of the anonymous referees.     

各向异性四阶偏微分方程耦合二阶偏微分方程的图像放大

针对增强图像中的弱边缘、细节纹理和消除二阶偏微分方程在图像平滑部分的阶梯效应问题,提出一种各向异性四阶偏微分方程耦合二阶偏微分方程的图像放大算法。算法通过像素的局部方差自适应约束阈值,实现图像中不同结构的各向异性四阶扩散,增强弱边缘和细节纹理,去除平滑部分阶梯效应,同时耦合改进的总变差方法和受梯度约束的冲激滤波器对边缘进行增强,放大算法采用双正交映射实现图像退化模型的约束。仿真实验证明该算法能够很好地增强边缘、细节和纹理,去除阶梯效应。与其他二阶偏微分方程放大算法比较,算法具有较好的主观视觉效果,算法放大图像的峰值信噪比(PSNR)和平均结构相似性测度(MSSIM)也高于其他二阶偏微分方程算法,其中平滑部分较多图像的PSNR比基于改进的总变差放大算法提高1 dB左右,细节纹理较多的图像提高0.5 dB以上。该算法的放大图像更加自然,弱边缘和细节能够得到分辨率增强。     

Unsupervised detection and localization of structural textures using projection profiles

The main goal of existing approaches for structural texture analysis has been the identification of repeating texture primitives and their placement patterns in images containing a single type of texture. We describe a novel unsupervised method for simultaneous detection and localization of multiple structural texture areas along with estimates of their orientations and scales in real images. First, multi-scale isotropic filters are used to enhance the potential texton locations. Then, regularity of the textons is quantified in terms of the periodicity of projection profiles of filter responses within sliding windows at multiple orientations. Next, a regularity index is computed for each pixel as the maximum regularity score together with its orientation and scale. Finally, thresholding of this regularity index produces accurate localization of structural textures in images containing different kinds of textures as well as non-textured areas. Experiments using three different data sets show the effectiveness of the proposed method in complex scenes.     

Guessing Tangents in Normal Flows

Given a flow field parallel to isophote normals, a normal flow field, we seek a unobservable tangential field as the minimum of a general energy functional of the total field. We generalize existing methods to any linear, differential operator order on the combined field while keeping the projection onto the isophote normal constant. We discuss invariant flow fields, present a novel iterative solution based on Euler-Lagrange equations, prove continuous convergence, and give synthetic examples for common energy functionals. Possible uses are: estimating physical flow in image sequences, estimating human growth processes, and co-warping textures in animation sequences.     

Texture Synthesis From Photographs

The goal of texture synthesis is to generate an arbitrarily large high‐quality texture from a small input sample. Generally, it is assumed that the input image is given as a flat, square piece of texture, thus it has to be carefully prepared from a picture taken under ideal conditions. Instead we would like to extract the input texture from any surface from within an arbitrary photograph. This introduces several challenges: Only parts of the photograph are covered with the texture of interest, perspective and scene geometry introduce distortions, and the texture is non‐uniformly sampled during the capture process. This breaks many of the assumptions used for synthesis. In this paper we combine a simple novel user interface with a generic per‐pixel synthesis algorithm to achieve high‐quality synthesis from a photograph. Our interface lets the user locally describe the geometry supporting the textures by combining rational Bézier patches. These are particularly well suited to describe curved surfaces under projection. Further, we extend per‐pixel synthesis to account for arbitrary texture sparsity and distortion, both in the input image and in the synthesis output. Applications range from synthesizing textures directly from photographs to high‐quality texture completion.