File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Multi-class blue noise sampling

TitleMulti-class blue noise sampling
Authors
KeywordsBlue noise
Dart throwing
Multi-class
Poisson hard/soft disk
Relaxation
Sampling
Issue Date2010
PublisherAssociation for Computing Machinery, Inc
Citation
Acm Transactions On Graphics, 2010, v. 29 n. 4 How to Cite?
AbstractSampling is a core process for a variety of graphics applications. Among existing sampling methods, blue noise sampling remains popular thanks to its spatial uniformity and absence of aliasing artifacts. However, research so far has been mainly focused on blue noise sampling with a single class of samples. This could be insufficient for common natural as well as man-made phenomena requiring multiple classes of samples, such as object placement, imaging sensors, and stippling patterns. We extend blue noise sampling to multiple classes where each individual class as well as their unions exhibit blue noise characteristics. We propose two flavors of algorithms to generate such multiclass blue noise samples, one extended from traditional Poisson hard disk sampling for explicit control of sample spacing, and another based on our soft disk sampling for explicit control of sample count. Our algorithms support uniform and adaptive sampling, and are applicable to both discrete and continuous sample space in arbitrary dimensions. We study characteristics of samples generated by our methods, and demonstrate applications in object placement, sensor layout, and color stippling. © 2010 ACM.
Persistent Identifierhttp://hdl.handle.net/10722/141787
ISSN
2015 Impact Factor: 4.218
2015 SCImago Journal Rankings: 2.552
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorWei, LYen_HK
dc.date.accessioned2011-09-27T03:01:58Z-
dc.date.available2011-09-27T03:01:58Z-
dc.date.issued2010en_HK
dc.identifier.citationAcm Transactions On Graphics, 2010, v. 29 n. 4en_HK
dc.identifier.issn0730-0301en_HK
dc.identifier.urihttp://hdl.handle.net/10722/141787-
dc.description.abstractSampling is a core process for a variety of graphics applications. Among existing sampling methods, blue noise sampling remains popular thanks to its spatial uniformity and absence of aliasing artifacts. However, research so far has been mainly focused on blue noise sampling with a single class of samples. This could be insufficient for common natural as well as man-made phenomena requiring multiple classes of samples, such as object placement, imaging sensors, and stippling patterns. We extend blue noise sampling to multiple classes where each individual class as well as their unions exhibit blue noise characteristics. We propose two flavors of algorithms to generate such multiclass blue noise samples, one extended from traditional Poisson hard disk sampling for explicit control of sample spacing, and another based on our soft disk sampling for explicit control of sample count. Our algorithms support uniform and adaptive sampling, and are applicable to both discrete and continuous sample space in arbitrary dimensions. We study characteristics of samples generated by our methods, and demonstrate applications in object placement, sensor layout, and color stippling. © 2010 ACM.en_HK
dc.languageengen_US
dc.publisherAssociation for Computing Machinery, Incen_US
dc.relation.ispartofACM Transactions on Graphicsen_HK
dc.subjectBlue noiseen_HK
dc.subjectDart throwingen_HK
dc.subjectMulti-classen_HK
dc.subjectPoisson hard/soft disken_HK
dc.subjectRelaxationen_HK
dc.subjectSamplingen_HK
dc.titleMulti-class blue noise samplingen_HK
dc.typeArticleen_HK
dc.identifier.emailWei, LY:lywei@cs.hku.hken_HK
dc.identifier.authorityWei, LY=rp01528en_HK
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1145/1778765.1778816en_HK
dc.identifier.scopuseid_2-s2.0-77956368735en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-77956368735&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume29en_HK
dc.identifier.issue4en_HK
dc.identifier.eissn1557-7368-
dc.identifier.isiWOS:000279806600049-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridWei, LY=14523963300en_HK

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats