The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Color image quantization for frame buffer display
Abstract
Algorithms for adaptive, tapered quantization of color images are described. The research is motivated by the desire to display high-quality reproductions of color images with small frame buffers. It is demonstrated that many color images which would normally require a frame buffer having 15 bits per pixel can be quantized to 8 or fewer bits per pixel with little subjective degradation. In most cases, the resulting images look significantly better than those made with uniform quantization. The color image quantization task is broken into four phases: 1) Sampling the original image for color statistics 2) Choosing a colormap based on the color statistics 3) Mapping original colors to their nearest neighbors in the colormap 4) Quantizing and redrawing the original image (with optional dither). Several algorithms for each of phases 2-4 are described, and images created by each given.
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Cites
An Algorithm for Finding Best Matches in Logarithmic Expected Time
Friedman, J. H., Bentley, J. L., & Finkel, R. A. (1977) · ACM Transactions on Mathematical Software · doi:10.1145/355744.355745 · Cited by 2,813
The Art of Computer Programming
Worlton, W. J. (1968) · Nuclear Science and Engineering · doi:10.13182/nse68-a19548 · Cited by 2,251
Quantizing for minimum distortion
Max, J. (1960) · IEEE Transactions on Information Theory · doi:10.1109/tit.1960.1057548 · Cited by 2,038
Data Structures for Range Searching
Bentley, J. L., & Friedman, J. H. (1979) · ACM Computing Surveys · doi:10.1145/356789.356797 · Cited by 622
A survey of techniques for the display of continuous tone pictures on bilevel displays
Jarvis, J. F., Judice, C. N., & Ninke, W. H. (1976) · Computer Graphics and Image Processing · doi:10.1016/s0146-664x(76)80003-2 · Cited by 564
Picture coding using pseudo-random noise
Roberts, L. (1962) · IEEE Transactions on Information Theory · doi:10.1109/tit.1962.1057702 · Cited by 339
Quantization Distortion in Pulse-Count Modulation with Nonuniform Spacing of Levels
Panter, P. F., & Dite, W. (1951) · Proceedings of the IRE · doi:10.1109/jrproc.1951.230419 · Cited by 225
A Branch and Bound Clustering Algorithm
Koontz, W. L. G., Narendra, P. M., & Fukunaga, K. (1975) · IEEE Transactions on Computers · doi:10.1109/t-c.1975.224336 · Cited by 197
Locally optimal block quantizer design
Gray, R. M., Kieffer, J. C., & Linde, Y. (1980) · Information and Control · doi:10.1016/s0019-9958(80)90313-7 · Cited by 136
Digital Coding of Color Video Signals--A Review
Limb, J. O., Rubinstein, C. B., & Thompson, J. E. (1977) · IRE Transactions on Communications Systems · doi:10.1109/tcom.1977.1093774 · Cited by 105
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Automated melanoma recognition
Ganster, H., Pinz, P., Rohrer, R., Wildling, E., Binder, M., & Kittler, H. (2001) · IEEE Transactions on Medical Imaging · doi:10.1109/42.918473 · Cited by 631
Sharma, G., & Trussell, H. J. (1997) · IEEE Transactions on Image Processing · doi:10.1109/83.597268 · Cited by 440
Convergence of the Lloyd Algorithm for Computing Centroidal Voronoi Tessellations
Du, Q., Emelianenko, M., & Ju, L. (2006) · SIAM Journal on Numerical Analysis · doi:10.1137/040617364 · Cited by 305
A Simple Method for Color Quantization: Octree Quantization
Gervautz, M., & Purgathofer, W. (1988) · New Trends in Computer Graphics · doi:10.1007/978-3-642-83492-9_20 · Cited by 290
Metadata
- Authors
- Heckbert, P.
- Venue
- ACM SIGGRAPH Computer Graphics
- Published
- 1982-07
- Volume
- 16
- Issue
- 3
- Pages
- 297-307
- ISSN
- 0097-8930 (ISSN-L)
- OpenAlex
- W3000042338
- Cited by
- 549
- References
- 11
- FWCI
- 1.38
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
