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Computing the Discrepancy with Applications to Supersampling Patterns (1996)
| Content Provider | CiteSeerX |
|---|---|
| Author | Dobkin, David P. Eppstein, David Mitchell, Don P. |
| Abstract | Patterns used for supersampling in graphics have been analyzed from statistical and signal-processing viewpoints. We present an analysis based on a type of isotropic discrepancy---how good patterns are at estimating the area in a region of defined type. We present algorithms for computing discrepancy relative to regions that are defined by rectangles, halfplanes, and higher-dimensional figures. Experimental evidence shows that popular supersampling patterns have discrepancies with better asymptotic behavior than random sampling, which is not inconsistent with theoretical bounds on discrepancy. |
| File Format | |
| Volume Number | 15 |
| Journal | ACM TRANSACTIONS ON GRAPHICS |
| Language | English |
| Publisher Date | 1996-01-01 |
| Access Restriction | Open |
| Subject Keyword | Supersampling Pattern Discrepancy Relative Higher-dimensional Figure Signal-processing Viewpoint Popular Supersampling Pattern Present Algorithm Asymptotic Behavior Defined Type Theoretical Bound Isotropic Discrepancy Experimental Evidence Show Good Pattern Random Sampling |
| Content Type | Text |
| Resource Type | Article |
