SIGGRAPH '86 Proceedings of the 13th annual conference on Computer graphics and interactive techniques
Generating antialiased images at low sampling densities
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
Antialiased ray tracing by adaptive progressive refinement
SIGGRAPH '89 Proceedings of the 16th annual conference on Computer graphics and interactive techniques
A course in fuzzy systems and control
A course in fuzzy systems and control
A framework for realistic image synthesis
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
A perceptually based adaptive sampling algorithm
Proceedings of the 25th annual conference on Computer graphics and interactive techniques
A framework for realistic image synthesis
Communications of the ACM
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
An improved illumination model for shaded display
Communications of the ACM
Adaptive Smpling and Bias Estimation in Path Tracing
Proceedings of the Eurographics Workshop on Rendering Techniques '97
Tapestry: A Dynamic Mesh-based Display Representation for Interactive Rendering
Proceedings of the Eurographics Workshop on Rendering Techniques 2000
Refinement criteria based on f-divergences
EGRW '03 Proceedings of the 14th Eurographics workshop on Rendering
Fuzziness driven adaptive sampling for monte carlo global illuminated rendering
CGI'06 Proceedings of the 24th international conference on Advances in Computer Graphics
IEEE Transactions on Image Processing
AM-GM difference based adaptive sampling for Monte Carlo global illumination
ICCSA'07 Proceedings of the 2007 international conference on Computational science and Its applications - Volume Part II
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Monte Carlo is the only choice for a physically correct method to do global illumination in the field of realistic image rendering. Adaptive sampling is an appealing means to reduce noise, which is resulted from the general Monte Carlo global illumination algorithms. In this paper, we take advantage of fuzzy rule-based reasoning to achieve different refinement thresholds for different pixels in the synthesized image. The developed technique can do adaptive sampling elaborately and effectively. Extensive implementation results indicate that our novel method can achieve significantly better than classic ones. To our knowledge, this is the first application of the fuzzy inference to global illumination.