一种高效体数据压缩算法及其在地震数据处理中的应用

采用可编程图形硬件对大规模体数据进行直接体绘制时常常受到图形卡容量的限制,导致数据在内存与显存之间频繁交换,从而成为绘制的瓶颈.为此,提出一种大规模体数据矢量量化压缩算法.首先对体数据分块,并依据块内数据平均梯度值是否为0对该块进行分类;然后用3层结构表示梯度值非0的块,对其中次高层和最高层采用基于主分量分析分裂法产生初始码书,用LBG算法进行码书优化和量化,而对最低层以及梯度值为0的块采用定比特量化.实验结果表明,在保证较好图像重构质量的前提下,该算法可获得50倍以上的压缩比和更快的解压速度.     

基于GPU Raycasting算法的矢量/栅格混合绘制研究*

Raycasting体绘制算法由于成像质量高而被广泛应用于体数据的可视化,但当线、面表达的矢量数据和三维栅格表达的体数据同时绘制到同一场景时,由于绘制方法的差异会造成矢量和栅格数据空间遮挡关系不一致。在GPU实现Raycasting算法的基础上,通过矢量和栅格数据先后绘制,采用FBO离屏绘制等技术将矢量数据绘制到深度缓存纹理并在体绘制采样和融合中统一考虑矢栅颜色融合。实验结果表明,该算法在矢量数据非透明模式下能正确处理矢量栅格数据的混合绘制。     

适用于GPU的四面体体数据规则化与可视化

为实现三维不规则体数据场的高效绘制,提出一种适用于GPU的四面体体数据规则化和可视化算法.将以四面体为基本单元的稀疏体数据用一个有限深度的八叉树结构逼近,并将逼近误差表达为一个离散的完全空间哈希结构;然后将半规则的八叉树转换为规则的八叉树纹理(三维),并将完全空间哈希表转换为三维查找表,两者均可在绘制时快速随机取值,故可直接作为三维纹理在GPU中访问.通过这种双规则化的表示方法,可将四面体体数据的可视化转化为在GPU中并行地绘制2种三维纹理.实验结果表明,该算法在处理空间稀疏体数据时保证了较高的精度,同时减少了数据存储量.     

基于最优化分块的大规模数据体绘制加速方法

GPU加速体绘制已成为体可视化领域的研究热点,然而超出显存的大规模数据无法直接载入,成为GPU应用的瓶颈。分块技术能够在保证图像质量的条件下解决该问题,但分块数据的频繁加载和访问明显降低了绘制速度。针对上述问题,通过建立最优化分块模型得到了大规模数据的最优分块,并通过构造节点编号纹理和改进距离模板设计的方法进一步提高了基于八叉树的分块体绘制算法的绘制速度。实验结果表明,该方法加速效果明显。     

数字人切片数据的硬件加速体绘制

实现了一个PC平台下的体绘制硬件加速算法,并对中国数字人、美国可视化人数据集进行可视化．预处理去除图像背景时,将图像从RGB颜色空间转换到YCbCr颜色空间,然后对Cb分量进行Otsu阈值化处理,用生成的二值图像作为掩码图像去除背景．为支持任意大小的体数据,采取了分块策略,并使用BSP树组织数据块,以生成正确的绘制顺序．此外还设计了一种基于图像的CIELUV颜色空间L分量的梯度向量场的传输函数,并取得了良好的绘制效果．     

基于GPU的实时光线投射算法

介绍了一种基于GPU（可编程图形处理单元）的快速实时光线投射算法。为满足大规模体数据集的绘制要求,利用当前GPU的新特性,直接将体数据作为纹理载入显存,采用预积分分类方法在GPU中对体数据进行重采样和分类,避免了计算机主内存与GPU纹理内存之间数据交换的瓶颈问题;利用硬件支持的三维纹理和片元着色器,实时计算每个体素的梯度,实现高质量的光照,保证高质量的图像绘制效果。实验结果表明该方法在医学三维数据场可视化中,能够实时、高效地生成高质量的交互式体可视化图像。     

改进的均匀数据场GPU光线投射

针对均匀数据场GPU光线投射技术中梯度、代理面和预积分计算存在的一些问题和多块绘制中可能存在缝隙的问题,设计了改进的GPU光线投射方法。主要改进有按需在物理空间实时计算梯度,估计梯度上界;单趟GPU预积分;设计体裁剪方法、缝隙消除方法。实验结果表明,改进的GPU光线投射技术便于采用梯度量调制,以突出感兴趣的物质; 可以交互修改转换函数,快速发现感兴趣的特征; 可以避免绘制错误;还可以逐步剥离前面的物体,看到后面的物体;可以对数据进行漫游; 绘制多块数据时没有缝隙。     

三维地形高质量实时矢量叠加绘制

在高低起伏的三维地形上无缝叠加二维矢量数据是三维地理信息系统可视化的必须功能.为了进一步提高矢量纹理的像素有效利用率,减轻走样,提出一种采用多级联的绘制方法来改进传统基于纹理的矢量叠加绘制过程的算法.该算法采用深度剖分和屏幕空间分块2种策略对视域四棱锥进行分割,对子四棱锥内矢量进行级联绘制,并对绘制范围进行调整优化,整个算法过程完整地利用了现代GPU可编程硬件来实现.实验结果表明,文中算法适用于大范围多分辨率地形上的矢量绘制,绘制过程达到了实时,绘制效果令人满意.     

基于数据流聚类策略的GPU码书初始化算法

码书生成是基于矢量量化压缩体绘制的关键之一。在码书生成中,初始码书对码书生成算法有较大的影响。现有的码书初始化方法需要对原始海量数据进行多次迭代,数据频繁在硬盘、内存和GPU（图形处理器）之间进行数据传输,导致算法效率不高。本文针对码书生成的初始码书提取问题,提出了基于数据流聚类策略的初始码书生成算法。其基本思想是将海量三维数据体当作一个数据流（分块）,对每一部分数据形成局部码书,再对所有的局部码书进行分类形成最终的初始码书。利用本方法可以极大的减少数据的读取和传输的次数,同时,充分利用GPU并行计算能力。通过仿真结果分析表明,本文提出的方法在效率上和效果上都有较大的提高。     

基于GPU光线投射算法的心脏体数据三维可视化

心脏成像和可视化技术在心脏疾病诊断、治疗规划中发挥着重要作用。针对分割后的心脏体数据集,提出了使用图形处理器(GPU)加速光线投射算法进行高质量三维可视化的新方法。该方法结合心脏体数据统计信息设计传递函数,增大细微组织的不透明度值;基于梯度模自适应地调整采样步长,提高组织边界的采样频率;应用改进的Blinn-Phong多光源光照模型,增强可视化效果。实验结果表明,该方法在实现实时绘制的同时,能够获得高质量的体绘制效果,渲染出清晰的瓣膜和冠状动脉血管等心脏细微组织。     

State‐of‐the‐Art in Compressed GPU‐Based Direct Volume Rendering

Great advancements in commodity graphics hardware have favoured graphics processing unit (GPU)‐based volume rendering as the main adopted solution for interactive exploration of rectilinear scalar volumes on commodity platforms. Nevertheless, long data transfer times and GPU memory size limitations are often the main limiting factors, especially for massive, time‐varying or multi‐volume visualization, as well as for networked visualization on the emerging mobile devices. To address this issue, a variety of level‐of‐detail (LOD) data representations and compression techniques have been introduced. In order to improve capabilities and performance over the entire storage, distribution and rendering pipeline, the encoding/decoding process is typically highly asymmetric, and systems should ideally compress at data production time and decompress on demand at rendering time. Compression and LOD pre‐computation does not have to adhere to real‐time constraints and can be performed off‐line for high‐quality results. In contrast, adaptive real‐time rendering from compressed representations requires fast, transient and spatially independent decompression. In this report, we review the existing compressed GPU volume rendering approaches, covering sampling grid layouts, compact representation models, compression techniques, GPU rendering architectures and fast decoding techniques.     

基于线性八叉树的光线投射体绘制算法改进研究

体视化是地学信息三维可视化研究的前沿技术之一，体绘制算法的效率直接关系到体视化的效果。本文在研究已有光线投射体绘制改进算法的基础上，提出利用线性八叉树数据结构对光线投射体绘制算法进行改进研究，不仅实现了体数据的压缩。而且能对压缩体数据进行直接体视化。在PC机上的实验表明，该方法具有时间复杂度与数据复杂度基本无关的特点．加速效果明显。最后，文章指出了该方法的适用范围。     

基于JPEG的固定背景视频压缩算法研究

为了对固定背景视频进行压缩并获得较高的压缩比,在JPEG静止图像压缩标准的基础上提出了一种新的应用于固定背景视频压缩的算法.对第一帧图像进行JPEG格式的压缩并保存量化后的离散余弦变换系数,对第一帧后的每一帧图像,在进行离散余弦变换和量化后,先同存储器内的第一帧图像的离散余弦变换系数进行异或运算再进行熵编码.通过使用该算法和H.264视频压缩标准对同一段固定背景视频进行压缩并比较压缩后的数据量,表明了该算法具有较高的压缩比.     

Volumetric video compression for interactive playback

We develop a volumetric video system which supports interactive browsing of compressed time-varying volumetric features (significant isosurfaces and interval volumes). Since the size of even one volumetric frame in a time-varying 3D data set is very large, transmission and on-line reconstruction are the main bottlenecks for interactive remote visualization of time-varying volume and surface data. We describe a compression scheme for encoding time-varying volumetric features in a unified way, which allows for on-line reconstruction and rendering. To increase the run-time decompression speed and compression ratio, we decompose the volume into small blocks and encode only the significant blocks that contribute to the isosurfaces and interval volumes. The results show that our compression scheme achieves high compression ratio with fast reconstruction, which is effective for interactive client-side rendering of time-varying volumetric features.     

Volume rendering of DCT-based compressed 3D scalar data

The paper proposes a scheme to perform volume rendering from compressed scalar data. Instead of decompressing the entire data set before rendering, blocks of data are decompressed as needed. Discrete cosine transform based compression technique is used to illustrate the method. The data is partitioned into overlapping blocks to permit local rendering and allow easy parallelization. Compression by factor of 20 to 30 produces rendering virtually indistinguishable from rendering using the original uncompressed data. Speedup is obtained by making use of spatial homogeneity detected in the transform domain. Rendering time using the proposed approach is less than that of direct rendering from the entire uncompressed data. The proposed method thus offers an attractive option to reduce storage, computation, and transmission overhead of otherwise huge data sets     

具有剪切的矢量压缩立体绘制算法

利用矢量压缩的方法进行立体绘制,一个不足是根据码本生成的Pixmap图无法应用于立体投影中的每一点,为了克服这些缺点,提出了具有Shear Warp的矢量化算法,它充分发挥了矢量量化的压缩比,以及不需要解压即可直接进行体绘制的优点,有效地利用了具有Shear Warp的体绘制方法的快速和适合立体投影的优点,克服了基于矢量量化的绘制方法的不足,几乎能够达到实时的交互绘制,是一种基于网络的绘制模式。     

No-reference image quality assessment based on localized discrete cosine transform for JPEG compressed images

In this paper, we propose a new no-reference image quality assessment for JPEG compressed images. In contrast to the most existing approaches, the proposed method considers the compression processes for assessing the blocking effects in the JPEG compressed images. These images have blocking artifacts in high compression ratio. The quantization of the discrete cosine transform (DCT) coefficients is the main issue in JPEG algorithm to trade-off between image quality and compression ratio. When the compression ratio increases, DCT coefficients will be further decreased via quantization. The coarse quantization causes blocking effect in the compressed image. We propose to use the DCT coefficient values to score image quality in terms of blocking artifacts. An image may have uniform and non-uniform blocks, which are respectively associated with the low and high frequency information. Once an image is compressed using JPEG, inherent non-uniform blocks may become uniform due to quantization, whilst inherent uniform blocks stay uniform. In the proposed method for assessing the quality of an image, firstly, inherent non-uniform blocks are distinguished from inherent uniform blocks by using the sharpness map. If the DCT coefficients of the inherent non-uniform blocks are not significant, it indicates that the original block was quantized. Hence, the DCT coefficients of the inherent non-uniform blocks are used to assess the image quality. Experimental results on various image databases represent that the proposed blockiness metric is well correlated with the subjective metric and outperforms the existing metrics.

     

基于角点检测的稳健图像摘要

图像摘要(Hash)是将数字图像映射为一串短的数,在图像认证、图像内容检索、数字水印等方面有广泛应用。提出了应用Harris角点检测和奇异值分解的图像Hash算法,首先在图像中选取对灰度变化和旋转稳健的Harris角点,对这些稳健特征点周围图像块的奇异值进行量化以实现数据压缩,经编码产生图像Hash。该算法建立在稳健特征点检测基础上,结合了特征点的位置和周围图像信息,得到的Hash对视觉可接受的几何变换、亮度和对比度变化、JPEG压缩具有良好的稳健性,而大幅度扰动或篡改则会改变Hash值。密钥的使用保证了Hash的安全性。     

Interactive multiscale tensor reconstruction for multiresolution volume visualization

Large scale and structurally complex volume datasets from high-resolution 3D imaging devices or computational simulations pose a number of technical challenges for interactive visual analysis. In this paper, we present the first integration of a multiscale volume representation based on tensor approximation within a GPU-accelerated out-of-core multiresolution rendering framework. Specific contributions include (a) a hierarchical brick-tensor decomposition approach for pre-processing large volume data, (b) a GPU accelerated tensor reconstruction implementation exploiting CUDA capabilities, and (c) an effective tensor-specific quantization strategy for reducing data transfer bandwidth and out-of-core memory footprint. Our multiscale representation allows for the extraction, analysis and display of structural features at variable spatial scales, while adaptive level-of-detail rendering methods make it possible to interactively explore large datasets within a constrained memory footprint. The quality and performance of our prototype system is evaluated on large structurally complex datasets, including gigabyte-sized micro-tomographic volumes.