A method for estimating the errors in many-light rendering with supersampling  

作　　者：Hirokazu Sakai Kosuke Nabata Shinya Yasuaki Kei Iwasaki 

机构地区：[1]Wakayama University,Wakayama,Wakayama,640-8510,Japan [2]Dwango CG Research,KADOKAWA Hongo Bldg.5245 Hongo,Bunkyo-ku,Tokyo,1130033,Japan

出　　处：《Computational Visual Media》2019年第2期151-160,共10页计算可视媒体（英文版）

基　　金：partially supported by JSPS KAKENHI 15H05924 and 18H03348

摘　　要：In many-light rendering, a variety of visual and illumination effects, including anti-aliasing,depth of field, volumetric scattering, and subsurface scattering, are combined to create a number of virtual point lights(VPLs). This is done in order to simplify computation of the resulting illumination. Naive approaches that sum the direct illumination from many VPLs are computationally expensive;scalable methods can be computed more efficiently by clustering VPLs, and then estimating their sum by sampling a small number of VPLs. Although significant speed-up has been achieved using scalable methods, clustering leads to uncontrollable errors, resulting in noise in the rendered images. In this paper, we propose a method to improve the estimation accuracy of manylight rendering involving such visual and illumination effects. We demonstrate that our method can improve the estimation accuracy by a factor of 2.3 over the previous method.In many-light rendering, a variety of visual and illumination effects, including anti-aliasing,depth of field, volumetric scattering, and subsurface scattering, are combined to create a number of virtual point lights(VPLs). This is done in order to simplify computation of the resulting illumination. Naive approaches that sum the direct illumination from many VPLs are computationally expensive; scalable methods can be computed more efficiently by clustering VPLs, and then estimating their sum by sampling a small number of VPLs. Although significant speed-up has been achieved using scalable methods, clustering leads to uncontrollable errors, resulting in noise in the rendered images. In this paper, we propose a method to improve the estimation accuracy of manylight rendering involving such visual and illumination effects. We demonstrate that our method can improve the estimation accuracy by a factor of 2.3 over the previous method.

关 键 词：ANTI-ALIASING DEPTH of field many-light RENDERING participating media 

分 类 号：TP[自动化与计算机技术]