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Article: Efficient Depth-of-Field Rendering with Adaptive Sampling and Multiscale Reconstruction

TitleEfficient Depth-of-Field Rendering with Adaptive Sampling and Multiscale Reconstruction
Authors
KeywordsAdaptive sampling
Depth-of-field rendering
I.3.3 [Computer Graphics]: Picture/Image Generation
I.3.7 [Computer Graphics]: Three-Dimensional Graphics and Realism
Multiscale reconstruction
Issue Date2011
PublisherBlackwell Publishing Ltd. The Journal's web site is located at http://www.blackwellpublishing.com/journals/CGF
Citation
Computer Graphics Forum, 2011 How to Cite?
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. © 2011 The Authors Computer Graphics Forum © 2011 The Eurographics Association and Blackwell Publishing Ltd..
Persistent Identifierhttp://hdl.handle.net/10722/140811
ISSN
2015 Impact Factor: 1.542
2015 SCImago Journal Rankings: 0.960
ISI Accession Number ID
Funding AgencyGrant Number
Chinese 973 Program2010CB328001
National Science Foundation of China61035002
ANR-NSFC60911130368
Chinese 863 Program2010AA186002
Tsinghua University2009THZ0
Fok Ying Tung Education Foundation111070
Funding Information:

The authors thank Peng Liu, Guidu Chen and the anonymous reviewers for their valuable comments and suggestions. The research was supported by Chinese 973 Program (2010CB328001), the National Science Foundation of China (61035002), the ANR-NSFC(60911130368) and Chinese 863 Program (2010AA186002). Prof. Yong was supported by Tsinghua University Initiative Scientific Research Program(2009THZ0) and the Fok Ying Tung Education Foundation (111070). The chess and pool scenes are from Hachisuka et al. [HJW*08], dragons and plants from PBRT[PH04], and the tree model in Figures 2 and 3 from Evermotion team (www.evermotion.org).

 

DC FieldValueLanguage
dc.contributor.authorChen, Jen_HK
dc.contributor.authorWang, Ben_HK
dc.contributor.authorWang, Yen_HK
dc.contributor.authorOverbeck, RSen_HK
dc.contributor.authorYong, JHen_HK
dc.contributor.authorWang, Wen_HK
dc.date.accessioned2011-09-23T06:19:35Z-
dc.date.available2011-09-23T06:19:35Z-
dc.date.issued2011en_HK
dc.identifier.citationComputer Graphics Forum, 2011en_HK
dc.identifier.issn0167-7055en_HK
dc.identifier.urihttp://hdl.handle.net/10722/140811-
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. © 2011 The Authors Computer Graphics Forum © 2011 The Eurographics Association and Blackwell Publishing Ltd..en_HK
dc.languageengen_US
dc.publisherBlackwell Publishing Ltd. The Journal's web site is located at http://www.blackwellpublishing.com/journals/CGFen_HK
dc.relation.ispartofComputer Graphics Forumen_HK
dc.rightsThe definitive version is available at www.blackwell-synergy.com-
dc.subjectAdaptive samplingen_HK
dc.subjectDepth-of-field renderingen_HK
dc.subjectI.3.3 [Computer Graphics]: Picture/Image Generationen_HK
dc.subjectI.3.7 [Computer Graphics]: Three-Dimensional Graphics and Realismen_HK
dc.subjectMultiscale reconstructionen_HK
dc.titleEfficient Depth-of-Field Rendering with Adaptive Sampling and Multiscale Reconstructionen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0167-7055&volume=30&issue=6&spage=1667&epage=1680&date=2011&atitle=Efficient+depth-of-field+rendering+with+adaptive+sampling+and+multiscale+reconstruction-
dc.identifier.emailWang, W:wenping@cs.hku.hken_HK
dc.identifier.authorityWang, W=rp00186en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1111/j.1467-8659.2011.01854.xen_HK
dc.identifier.scopuseid_2-s2.0-79953264519en_HK
dc.identifier.hkuros194923en_US
dc.identifier.volume30-
dc.identifier.issue6-
dc.identifier.spage1667-
dc.identifier.epage1680-
dc.identifier.isiWOS:000295129100006-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridChen, J=35145279600en_HK
dc.identifier.scopusauthoridWang, B=36014295200en_HK
dc.identifier.scopusauthoridWang, Y=37065469300en_HK
dc.identifier.scopusauthoridOverbeck, RS=14822559900en_HK
dc.identifier.scopusauthoridYong, JH=13907549600en_HK
dc.identifier.scopusauthoridWang, W=35147101600en_HK

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