Stochastic sampling in computer graphics
ACM Transactions on Graphics (TOG)
The Effect of Median Filtering on Edge Estimation and Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Generating antialiased images at low sampling densities
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
Statistically optimized sampling for distributed ray tracing
SIGGRAPH '85 Proceedings of the 12th annual conference on Computer graphics and interactive techniques
Antialiasing through stochastic sampling
SIGGRAPH '85 Proceedings of the 12th annual conference on Computer graphics and interactive techniques
The aliasing problem in computer-generated shaded images
Communications of the ACM
Perceptual color spaces for computer graphics
SIGGRAPH '80 Proceedings of the 7th annual conference on Computer graphics and interactive techniques
Synthetic texturing using digital filters
SIGGRAPH '80 Proceedings of the 7th annual conference on Computer graphics and interactive techniques
Three-dimensional medical imaging: algorithms and computer systems
ACM Computing Surveys (CSUR)
Energy preserving non-linear filters
SIGGRAPH '94 Proceedings of the 21st annual conference on Computer graphics and interactive techniques
SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
Anisotropic diffusion for Monte Carlo noise reduction
ACM Transactions on Graphics (TOG)
A Novel Monte Carlo Noise Reduction Operator
IEEE Computer Graphics and Applications
On filtering the noise from the random parameters in Monte Carlo rendering
ACM Transactions on Graphics (TOG)
Boosting monte carlo rendering by ray histogram fusion
ACM Transactions on Graphics (TOG)
| Hi-index | 0.00 |
The application of nonlinear median and alpha-trimmed mean filters to computer graphics is discussed. The filters are simple to implement, do not require large amounts of CPU time to execute, and can be applied iteratively for better control over the filtering effects. A series of examples shows that the filters eliminate spike noise in a stochastic sampling application without smearing the final image.