Article: Differential domain analysis for non-uniform sampling
| Title | Differential domain analysis for non-uniform sampling | ||||
|---|---|---|---|---|---|
| Authors | Wei, LY2 Wang, R1 | ||||
| Keywords | Analysis Differential domain Noise Non-uniform Sampling Spectrum | ||||
| Issue Date | 2011 | ||||
| Publisher | Association for Computing Machinery, Inc. The Journal's web site is located at http://tog.acm.org | ||||
| Citation | ACM Transactions on Graphics, 2011, v. 30 n. 4, article no. 50, p. 50:1-50:10 [How to Cite?] DOI: http://dx.doi.org/10.1145/1964921.1964945 | ||||
| Abstract | Sampling is a core component for many graphics applications including rendering, imaging, animation, and geometry processing. The efficacy of these applications often crucially depends upon the distribution quality of the underlying samples. While uniform sampling can be analyzed by using existing spatial and spectral methods, these cannot be easily extended to general non-uniform settings, such as adaptive, anisotropic, or non-Euclidean domains. We present new methods for analyzing non-uniform sample distributions. Our key insight is that standard Fourier analysis, which depends on samples' spatial locations, can be reformulated into an equivalent form that depends only on the distribution of their location differentials. We call this differential domain analysis. The main benefit of this reformulation is that it bridges the fundamental connection between the samples' spatial statistics and their spectral properties. In addition, it allows us to generalize our method with different computation kernels and differential measurements. Using this analysis, we can quantitatively measure the spatial and spectral properties of various non-uniform sample distributions, including adaptive, anisotropic, and non-Euclidean domains. © 2011 ACM. | ||||
| Description | Proceedings of ACM SIGGRAPH '11 Special Interest Group on Computer Graphics and Interactive Techniques Conference, Vancouver, BC, Canada, 7-11 August 2011 | ||||
| ISSN | 0730-0301 2011 Impact Factor: 3.489 2011 SCImago Journal Rankings: 0.093 | ||||
| DOI | http://dx.doi.org/10.1145/1964921.1964945 | ||||
| ISI Accession Number ID | WOS:000297216400024
Funding Information: We would like to thank Hongwei Li for clarifying details in [Li et al. 2010], and SIGGRAPH anonymous reviewers for their suggestions. This work is supported in part by NSF grant CCF-0746577. | ||||
| References | References in Scopus |
| dc.contributor.author | Wei, LY | ||||
|---|---|---|---|---|---|
| dc.contributor.author | Wang, R | ||||
| dc.date.accessioned | 2011-09-27T03:02:15Z | ||||
| dc.date.available | 2011-09-27T03:02:15Z | ||||
| dc.date.issued | 2011 | ||||
| dc.description.abstract | Sampling is a core component for many graphics applications including rendering, imaging, animation, and geometry processing. The efficacy of these applications often crucially depends upon the distribution quality of the underlying samples. While uniform sampling can be analyzed by using existing spatial and spectral methods, these cannot be easily extended to general non-uniform settings, such as adaptive, anisotropic, or non-Euclidean domains. We present new methods for analyzing non-uniform sample distributions. Our key insight is that standard Fourier analysis, which depends on samples' spatial locations, can be reformulated into an equivalent form that depends only on the distribution of their location differentials. We call this differential domain analysis. The main benefit of this reformulation is that it bridges the fundamental connection between the samples' spatial statistics and their spectral properties. In addition, it allows us to generalize our method with different computation kernels and differential measurements. Using this analysis, we can quantitatively measure the spatial and spectral properties of various non-uniform sample distributions, including adaptive, anisotropic, and non-Euclidean domains. © 2011 ACM. | ||||
| dc.description.nature | link_to_subscribed_fulltext | ||||
| dc.description | Proceedings of ACM SIGGRAPH '11 Special Interest Group on Computer Graphics and Interactive Techniques Conference, Vancouver, BC, Canada, 7-11 August 2011 | ||||
| dc.identifier.citation | ACM Transactions on Graphics, 2011, v. 30 n. 4, article no. 50, p. 50:1-50:10 [How to Cite?] DOI: http://dx.doi.org/10.1145/1964921.1964945 | ||||
| dc.identifier.doi | http://dx.doi.org/10.1145/1964921.1964945 | ||||
| dc.identifier.eissn | 1557-7368 | ||||
| dc.identifier.hkuros | 206832 | ||||
| dc.identifier.isi | WOS:000297216400024
Funding Information: We would like to thank Hongwei Li for clarifying details in [Li et al. 2010], and SIGGRAPH anonymous reviewers for their suggestions. This work is supported in part by NSF grant CCF-0746577. | ||||
| dc.identifier.issn | 0730-0301 2011 Impact Factor: 3.489 2011 SCImago Journal Rankings: 0.093 | ||||
| dc.identifier.issue | 4 | ||||
| dc.identifier.scopus | eid_2-s2.0-80051890935 | ||||
| dc.identifier.uri | http://hdl.handle.net/10722/141807 | ||||
| dc.identifier.volume | 30 | ||||
| dc.language | eng | ||||
| dc.publisher | Association for Computing Machinery, Inc. The Journal's web site is located at http://tog.acm.org | ||||
| dc.publisher.place | United States | ||||
| dc.relation.ispartof | ACM Transactions on Graphics | ||||
| dc.relation.references | References in Scopus | ||||
| dc.subject | Analysis | ||||
| dc.subject | Differential domain | ||||
| dc.subject | Noise | ||||
| dc.subject | Non-uniform | ||||
| dc.subject | Sampling | ||||
| dc.subject | Spectrum | ||||
| dc.title | Differential domain analysis for non-uniform sampling | ||||
| dc.type | Article |
Author Affiliations
- University of Massachusetts Amherst
- Microsoft Research