Efficient Depth‐of‐Field Rendering with Adaptive Sampling and Multiscale Reconstruction

dc.contributor.authorChen, Jiatingen_US
dc.contributor.authorWang, Binen_US
dc.contributor.authorWang, Yuxiangen_US
dc.contributor.authorOverbeck, Ryan S.en_US
dc.contributor.authorYong, Jun‐Haien_US
dc.contributor.authorWang, Wenpingen_US
dc.contributor.editorEduard Groeller and Holly Rushmeieren_US
dc.date.accessioned2015-02-27T16:09:09Z
dc.date.available2015-02-27T16:09:09Z
dc.date.issued2011en_US
dc.description.abstractDepth‐of‐field is one of the most crucial rendering effects for synthesizing photorealistic images. Unfortunately, this effect is also extremely costly. It can take hundreds to thousands of samples to achieve noise‐free results using Monte Carlo integration. This paper introduces an efficient adaptive depth‐of‐field rendering algorithm that achieves noise‐free results using significantly fewer samples. Our algorithm consists of two main phases: adaptive sampling and image reconstruction. In the adaptive sampling phase, the adaptive sample density is determined by a ‘blur‐size’ map and ‘pixel‐variance’ map computed in the initialization. In the image reconstruction phase, based on the blur‐size map, we use a novel multiscale reconstruction filter to dramatically reduce the noise in the defocused areas where the sampled radiance has high variance. Because of the efficiency of this new filter, only a few samples are required. With the combination of the adaptive sampler and the multiscale filter, our algorithm renders near‐reference quality depth‐of‐field images with significantly fewer samples than previous techniques.en_US
dc.description.number6
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume30
dc.identifier.doi10.1111/j.1467-8659.2011.01854.xen_US
dc.identifier.issn1467-8659en_US
dc.identifier.urihttps://doi.org/10.1111/j.1467-8659.2011.01854.xen_US
dc.publisherThe Eurographics Association and Blackwell Publishing Ltd.en_US
dc.titleEfficient Depth‐of‐Field Rendering with Adaptive Sampling and Multiscale Reconstructionen_US
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