一种二维矢量图形的硬件优化渲染算法

提出了一种适用于嵌入式设备的二维矢量图形硬件优化渲染算法。在采用超采样反锯齿模式下,该算法中每个像素点只使用一个方向权重计数器,而并非以往算法中每个像素点使用多个计数器,从而达到节省硬件资源,并大幅减少渲染所需计算量的效果。实验结果表明,和以往算法相比,在8-queen超采样模式和XVGA显示大小下,能节省83%的存储器使用量和65%的存储器访问量,并且能取得较好的反锯齿效果。     

A Family of Inexpensive Sampling Schemes

To improve image quality in computer graphics, antialiazing techniques such as supersampling and multisampling are used. We explore a family of inexpensive sampling schemes that cost as little as 1.25 samples per pixel and up to 2.0 samples per pixel. By placing sample points in the corners or on the edges of the pixels, sharing can occur between pixels, and this makes it possible to create inexpensive sampling schemes. Using an evaluation and optimization framework, we present optimized sampling patterns costing 1.25, 1.5, 1.75 and 2.0 samples per pixel.     

Object‐order template‐based approach for stereoscopic volume rendering

Stereoscopic volume rendering provides powerful depth information, but it takes a long time to render two‐eye images. Previous algorithms based on reprojection methods project the result of one view of a stereo pair into the other instead of rendering a new one completely. Because of inaccurate mapping between the two images, the quality of the reprojected image is not satisfactory. This paper presents a new algorithm to preserve the accuracy of both images with very little increase in computation time. The efficiency of the new algorithm comes from the use of ray templates and object‐order processing. This algorithm makes two different templates for each eye and renders two images simultaneously, tracing the volume only once in object order. We also extend the algorithm to support image‐space supersampling by using more ray templates. Experimental results show that the image quality of the new algorithm is not only comparable with that of ray casting but also the rendering speed is near that of the interactive shear–warp algorithm employing object‐order processing and spatial data coherency. Copyright © 1999 John Wiley & Sons, Ltd.     

Adaptive Supersampling in Object Space Using Pyramidal Rays

We introduce a new approach to three important problems in ray tracing: antialiasing, distributed light sources, and fuzzy reflections of lights and other surfaces. For antialiasing, our approach combines the quality of supersampling with the advantages of adaptive supersampling. In adaptive supersampling, the decision to partition a ray is taken in image-space , which means that small or thin objects may be missed entirely. This is particularly problematic in animation, where the intensity of such objects may appear to vary. Our approach is based on considering pyramidal rays (pyrays) formed by the viewpoint and the pixel. We test the proximity of a pyray to the boundary of an object, and if it is close (or marginal), the pyray splits into 4 sub-pyrays; this continues recursively with each marginal sub-pyray until the estimated change in pixel intensity is sufficiently small.
The same idea also solves the problem of soft shadows from distributed light sources, which can be calculated to any required precision. Our approach also enables a method of defocusing reflected pyrays, thereby producing realistic fuzzy reflections of light sources and other objects. An interesting byproduct of our method is a substantial speedup over regular supersampling even when all pixels are supersampled. Our algorithm was implemented on polygonal and circular objects, and produced images comparable in quality to stochastic sampling, but with greatly reduced run times.     

The Priority Face Determination Tree for Hidden Surface Removal

Many virtual environments are built from a set of polygons that form the basis of objects in the scene. Using priority-list algorithms, the sequence in which these polygons are drawn is dependent upon the location of an observer; the polygons must be ordered correctly before a realistic image can be displayed. It is necessary for a scene to be drawn correctly in real time from all locations before the observer can move interactively around the scene with complete freedom.
The binary-space partitioning (BSP) tree developed by Fuchs, Kedem and Naylor in 1980 stores the view independent priority of a set of polygons which can be used to obtain the correct order for any given view-point. However, the number of polygons grows significantly due to the BSP splitting stage, increasing the number of nodes in the tree. This affects linearly the number of tests necessary to traverse the tree to obtain the priority of the set of polygons.
The algorithm presented here is built using its associated BSP tree, but attempts to reduce the number of tests to, log_4/3 n , at the cost of a tree of size of O ( N 1.5^{log4/3 n −1}), where n is the initial number of polygons in the scene, and N the resulting number after BSP splitting. To achieve the increase in run-time efficiency, a height plane is used to restrict the view point of the observer to a fixed height, but the key to the efficiency of the algorithm is in the use of polygonal dependencies . In the scene; if we know our location relative to the front or back of a polygon, then our position relative to one-quarter of the remaining polygons, in the expected worst-case, can be determined.