The DOI matches its Crossref record.
A progressive refinement approach to fast radiosity image generation
Open accessAbstract
A reformulated radiosity algorithm is presented that produces initial images in time linear to the number of patches. The enormous memory costs of the radiosity algorithm are also eliminated by computing form-factors on-the-fly. The technique is based on the approach of rendering by progressive refinement. The algorithm provides a useful solution almost immediately which progresses gracefully and continuously to the complete radiosity solution. In this way the competing demands of realism and interactivity are accommodated. The technique brings the use of radiosity for interactive rendering within reach and has implications for the use and development of current and future graphics workstations.
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Citations
Cited by
The State of the Art in Interactive Global Illumination
Ritschel, T., Dachsbacher, C., Grosch, T., & Kautz, J. (2012) · Computer Graphics Forum · doi:10.1111/j.1467-8659.2012.02093.x · Cited by 132
Rendering Techniques for Computer-Aided Design
Feldman, S. (1994) · SMPTE Journal · doi:10.5594/j09713 · Cited by 2
Metadata
- Authors
- Cohen, M. F., Chen, S. E., Wallace, J. R., & Greenberg, D. P.
- Venue
- ACM SIGGRAPH Computer Graphics
- Published
- 1988-06
- Volume
- 22
- Issue
- 4
- Pages
- 75-84
- ISSN
- 0097-8930 (ISSN-L)
- OpenAlex
- W2023237845
- Cited by
- 532
- References
- 0
- FWCI
- 26.74
- Type
- journal article
- Language
- en
- Open access
- bronze
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- CoChat. (2026). Citation check: A progressive refinement approach to fast radiosity image generation. https://app.cochat.ai/papers/10.1145/378456.378487
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- Cohen, M. F., Chen, S. E., Wallace, J. R., & Greenberg, D. P. (1988). A progressive refinement approach to fast radiosity image generation. ACM SIGGRAPH Computer Graphics. https://doi.org/10.1145/378456.378487
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.