In an animated scene,geometry and lighting often change in an unpredictable way. Rendering algorithms based on Monte Carlo methods are usually employed to precisely capture all features of an animated scene. However,M...In an animated scene,geometry and lighting often change in an unpredictable way. Rendering algorithms based on Monte Carlo methods are usually employed to precisely capture all features of an animated scene. However,Monte Carlo methods typically take a long time to produce a noise-free image. In this paper,we propose a variance reduction technique for Monte Carlo methods which exploits coherence between frames. Firstly,we introduce a dual cone model to measure the incident coherence intersecting camera rays in object space. Secondly,we allocate multiple frame buffers to store image samples from consecutive frames. Finally,the color of a pixel in one frame is computed by borrowing samples from neighboring pixels in current,previous,and subsequent frames. Our experiments show that noise is greatly reduced by our method since the number of effective samples is increased by use of borrowed samples.展开更多
文摘In an animated scene,geometry and lighting often change in an unpredictable way. Rendering algorithms based on Monte Carlo methods are usually employed to precisely capture all features of an animated scene. However,Monte Carlo methods typically take a long time to produce a noise-free image. In this paper,we propose a variance reduction technique for Monte Carlo methods which exploits coherence between frames. Firstly,we introduce a dual cone model to measure the incident coherence intersecting camera rays in object space. Secondly,we allocate multiple frame buffers to store image samples from consecutive frames. Finally,the color of a pixel in one frame is computed by borrowing samples from neighboring pixels in current,previous,and subsequent frames. Our experiments show that noise is greatly reduced by our method since the number of effective samples is increased by use of borrowed samples.
