Vectorizing NURBS surface evaluation with basis functions in power basis

Several known methods for direct evaluation of NURBS curves and surfaces are described. Runtime performance and simplicity of vectorization are discussed. An evaluation method, which uses basis functions precomputed in shifted power basis, is shown to be promising. This method for surfaces is vectorized with SSE2 intrinsics, yielding 3 times performance improvement over the non-vectorized version. Branchless vectorized linear search is proposed for span search, being most efficient for small number of knots. Binary search ending with a small linear search is shown to be most efficient for large number of knots, and good for general case. Performance comparison of the evaluation method and its equivalents from available geometric kernels is included.     

Shadow allometry: Estimating tree structural parameters using hyperspatial image analysis

We present a novel approach to generating regional scale aboveground biomass estimates for tree species of the Lake Tahoe Basin using hyperspatial (< 1 m² ground resolution) remote sensing imagery. Tree crown shadows were identified and delineated as individual polygons. The area of shadowed vegetation for each tree was related to two tree structural parameters, diameter-at-breast height (DBH) and crown area. We found we could detect DBH and crown area with reasonable accuracy (field measured to image derived cross correlation results were 0.67 and 0.77 for DBH and crown area, respectively). Furthermore, the counts of the delineated polygons in a region generated overstory stem densities validated to manually photointerpreted stem densities (photointerpreted vs. image-derived stem densities correlation was 0.87). We demonstrate with accurate classification maps and allometric equations relating DBH or crown area to biomass, that these crown-level parameters can be used to generate regional scale biomass estimates without the signal saturation common to coarse-scale optical and RADAR sensors.     

A protocol for performance evaluation of line detection algorithms

Accurate and efficient vectorization of line drawings is essential for any higher level processing in document analysis and recognition systems. In spite of the prevalence of vectorization and line detection methods, no standard for their performance evaluation protocol exists. We propose a protocol for evaluating both straight and circular line extraction to help compare, select, improve, and even design line detection algorithms to be incorporated into line drawing recognition and understanding systems. The protocol involves both positive and negative sets of indices, at pixel and vector levels. Time efficiency is also included in the protocol. The protocol may be extended to handle lines of any shape as well as other classes of graphic objects.     

基于ICT图像矢量化处理的研究

论述了基于ICT图像进行矢量化处理的重要性矢量化处理的定义和基本过程，针对其中轮廓提取进行了详细的分析，包括边缘检测、轮廓跟踪、坐标标定和数据优化等内容。     

程序自动并行化系统

有效的自动并行化系统能帮助用户充分地利用并行计算机资源．本文介绍了自动并行化的历史及现状，并着重介绍了作者所开发的自动并行化系统ＡＦＴ（ａｕｔｏｍａｔｉｃＦｏｒｔｒａｎｔｒａｎｓｆｏｒｍｅｒ）及其特色和所用的关键技术．测试结果表明ＡＦＴ系统在功能上已超越了传统的自动并行化系统．     

一种快速的扫描铅笔稿图细化算法

二维动画计算机输助制作系统中,在对扫描铅笔稿图进行矢量化后,可以大大提高描线上色的效率,并且能够提取线条和闭包,对便于自动上色和中间帧生成等更高级功能的实现。扫描铅笔搞图的细化是矢量化的第一步,在比较了大量现存的图象细化算法后,提出了一种非迭代线跟踪细化算法,该算法效率较高,只需对图象进行一遍扫描加两遍轮廓跟踪,就能较好地满足二维动画计算机辅助制作系统对细化效率的要求。该文还对算法的时间复杂性进行     

基于Canny优化的卡通视频分割与矢量化

矢量化的视频图像相对于光栅化的视频图像具有储存容量小、缩放不失真等诸多优点。相对于真实视频,卡通视频因色块明显、线条清晰等特点更适合于进行矢量化处理。基于卡通的特性提出了一种基于Canny边缘检测的优化分割算法。主要针对Canny边缘提取不封闭的特点进行优化,并将其用于图像分割。提出了一种算法来提取卡通动画的素材,并为卡通动画构建素材库。通过素材重用的方式大大地缩小了卡通视频的储存空间,并且很好地解决了卡通视频矢量化问题中极易产生的帧间不一致的问题。实现了一个全自动地进行卡通视频矢量化的系统,其中包括卡通视频的镜头分割、素材库的构建等过程。该系统能够适应多种卡通视频,并能对视频中的细节区域产生较好的效果。     

SIMD向量指令的非满载使用方法研究

大规模SIMD体系结构提供了更强的向量并行硬件支持,但是,大量迭代次数不足的循环由于不能提供足够的并行性,难以用等价的向量方式实现。为了更有效地利用SIMD,提出了一种非满载地使用SIMD指令的向量化方法。研究了向量寄存器的使用方式,基于非满载的向量寄存器使用方式实现了非满载的向量操作和短循环的向量化,并将非满载的向量化方法用于一般循环的向量化。提供了收益分析方法来为本向量化方法作精确指导。实验结果表明了该方法的有效性,所选测试用例的目标循环被向量化,平均加速比达到1.2。     

SIMD代码中的向量访存优化研究

向量程序来源于手工编写或由编译器自动生成。受限于编程人员和并行编译器的能力,得到的向量程序都存在一定的优化空间。优化编译器通常关注如何将串行程序向量化,但很少对向量程序进行优化。因此,提出了一种针对SIMD代码的向量访存优化方法。该方法首先分析程序是否需要优化,若存在需求,则对程序同时进行深度冗余优化和对齐优化。实验数据显示,提出的方法可以明显提高程序的运行效率,达到了目标。