- 1.Vision texture library. MIT Media Lab. http://wwwwhite.media.mit.edu/vismod/imagery/VisionTexture/.Google Scholar
- 2.BLINN, J., AND NEWELL, M. Texture and reflection in computer generated images. Communications of the ACM 19,10 (October 1976), 542-547. Google ScholarDigital Library
- 3.BOLIN, M. R., AND MEYER, G. W. A perceptually based adaptive sampling algorithm. Proceedings of SIGGRAPH 98 (July 1998), 299-309. Google ScholarDigital Library
- 4.DANA, K., VAN GINNEKEN, B., NAYAR, S., AND KOEN- DERINK, J. Reflectance and texture of real world surfaces. ACM Transactions on Graphics 18, 1 (January 1999), 1-34. Google ScholarDigital Library
- 5.DEBONET, J. S. Multiresolution sampling procedure for analysis and synthesis of texture images. Proceedings of SIG- GRAPH 97 (August 1997), 361-368. Google ScholarDigital Library
- 6.DISCHLER, J.-M., AND GHAZANFARPOUR, D. Interactive image-based modeling of macrostructured textures. IEEE Computer Graphics and Applications 19, 1 (January- February 1999), 66-74. Google ScholarDigital Library
- 7.EFROS, A., AND LEUNG, T. Texture synthesis by nonparametric sampling. International Conference on Computer Vision 2 (September 1999), 1033-1038. Google ScholarDigital Library
- 8.HARALICK, R. Statistical image texture analysis. In Handbook of Pattern Recognition and Image Processing, vol. 86. Academic Press, June 1986, pp. 247-279.Google Scholar
- 9.HEEGER, D. J., AND BERGEN, J. R. Pyramid-based texture analysis/synthesis. In Proceedings of SIGGRAPH 95 (Anaheim, California, August 6-11, 1995) (August 1995), R. Cook, Ed., Computer Graphics Proceedings, Annual Conference Series, pp. 229-238. Google ScholarDigital Library
- 10.MIYATA, K. A method of generating stone wall patterns. Computer Graphics 24, 3 (August 1990), 387-394. ACM Siggraph '90 Conference Proceedings. Google ScholarDigital Library
- 11.PERLIN, K. An image synthesizer. Computer Graphics 19, 3 (July 1985), 287-296. ACM SIGGRAPH 85 Conference Proceedings. Google ScholarDigital Library
- 12.PERLIN, K., AND HOFFERT, E. M. Hypertexture. Computer Graphics 23, 3 (July 1989), 253-262. ACM SIGGRAPH 89 Conference Proceedings. Google ScholarDigital Library
- 13.PORTILLA, J., AND SIMONCELLI, E. P. A parametric texture model based on joint statistics of complex wavelet coefficients. International Journal of Computer Vision 39, 3 (October 2000). to appear. Google ScholarDigital Library
- 14.PRAUN, E., FINKELSTEIN, A., AND HOPPE, H. Lapped textures. Proceedings of SIGGRAPH 2000 (July 2000), 465- 470. Google ScholarDigital Library
- 15.RAMASUBRAMANIAN, M., PATTANAIK, S. N., AND GREENBERG, D. P. Perceptually based physical error metric for realistic image synthesis. Proceedings of SIGGRAPH 99 (August 1999), 73-82. Google ScholarDigital Library
- 16.WEI, L.-Y., AND LEVOY, M. Fast texture synthesis using tree-structured vector quantization. Proceedings of SIG- GRAPH 2000 (July 2000), 479-488. Google ScholarDigital Library
- 17.WITKIN, A., AND KASS, M. Reaction-diffusion textures. In Computer Graphics (SIGGRAPH '91 Proceedings) (July 1991), T. W. Sederberg, Ed., vol. 25, pp. 299-308. Google ScholarDigital Library
- 18.XU, Y., GUO, B., AND SHUM, H.-Y. Chaos mosaic: Fast and memory efficient texture synthesis. Tech. Rep. MSR-TR- 2000-32, Microsoft Research, 2000.Google Scholar
Index Terms
- Synthesizing natural textures
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