Antialiased ray tracing by adaptive progressive refinement

J. Painter, K. Sloan
{"title":"Antialiased ray tracing by adaptive progressive refinement","authors":"J. Painter, K. Sloan","doi":"10.1145/74333.74362","DOIUrl":null,"url":null,"abstract":"We describe an antialiasing system for ray tracing based on adaptive progressive refinement. The goals of the system are to produce high quality antialiased images at a modest average sample rate, and to refine the image progressively so that the image is available in a usable form early and is refined gradually toward the final result.The method proceeds by adaptive stochastic sampling of the image plane, evaluation of the samples by ray tracing, and image reconstruction from the samples. Adaptive control of the sample generation process is driven by three basic goals: coverage of the image, location of features, and confidence in the values at a distinguished \"pixel level\" of resolution.A three-stage process of interpolation, filtering, and resampling is used to reconstruct a regular grid of display pixels. This reconstruction can be either batch or incremental.","PeriodicalId":422743,"journal":{"name":"Proceedings of the 16th annual conference on Computer graphics and interactive techniques","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1989-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"199","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 16th annual conference on Computer graphics and interactive techniques","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/74333.74362","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 199

Abstract

We describe an antialiasing system for ray tracing based on adaptive progressive refinement. The goals of the system are to produce high quality antialiased images at a modest average sample rate, and to refine the image progressively so that the image is available in a usable form early and is refined gradually toward the final result.The method proceeds by adaptive stochastic sampling of the image plane, evaluation of the samples by ray tracing, and image reconstruction from the samples. Adaptive control of the sample generation process is driven by three basic goals: coverage of the image, location of features, and confidence in the values at a distinguished "pixel level" of resolution.A three-stage process of interpolation, filtering, and resampling is used to reconstruct a regular grid of display pixels. This reconstruction can be either batch or incremental.
自适应渐进细化的抗锯齿光线跟踪
描述了一种基于自适应渐进细化的光线跟踪抗混叠系统。该系统的目标是以适度的平均采样率产生高质量的抗混叠图像,并逐步细化图像,以便图像在早期以可用的形式可用,并逐步细化到最终结果。该方法首先对图像平面进行自适应随机采样,通过射线追踪对样本进行评估,然后对样本进行图像重建。样本生成过程的自适应控制由三个基本目标驱动:图像的覆盖范围、特征的位置和对分辨率的“像素级”值的置信度。一个三个阶段的过程插值,滤波和重采样是用来重建一个规则的网格的显示像素。这种重构可以是批处理的,也可以是增量的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信