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Antialiasing by Gaussian Integration
May 1996 (vol. 16 no. 3)
pp. 58-63
Typically, antialiasing is studied using Fourier spectrum analysis. A new conceptualization based on approximation theory is presented. Instead of viewing aliasing as a signal reconstruction problem we look at it as a general integral approximating a sampled function. With this attitude, a new method of antialiasing based on Gaussian integration is developed. Experiments show that this method may be preferrable when the number of sampling points is 9 points/pixel or more. We also show that the well-known Jittered Sampling methods are a special case of the new theory.

1. F.C. Crow, “The Problem in Computer-Generated Shaded Images,” Comm. ACM, vol. 20, no. 11, pp. 799-805, Nov. 1977.
2. R.L. Cook,“Stochastic sampling in computer graphics,” ACM Trans. on Graphics, vol. 5, no. 1, pp. 51-72, Jan. 1986.
3. F.J. Beutler, "Alias-Free Randomly Timed Sampling of Stochastic Processes," IEEE Trans. Information Theory, vol. 16, no. 2, pp. 147-152, Mar. 1970.
4. J.F. Blinn, "Jim Blinn's Corner: What We Need Around Here Is More Aliasing," IEEE CG&A, Vol. 9, No. 1, Jan. 1989, pp. 75-79.
5. J.F. Blinn, "Jim Blinn's Corner: Return of the Jaggy," IEEE CG&A, Vol. 9, No. 2, Mar. 1989, pp. 82-89.
6. J.C. Whitaker, Electronic Displays: Technology, Design, and Applications,McGraw-Hill, New York, 1994.
7. J.M. Cychosz, "Efficient Generation of Sampling Jitter Using Look-Up Tables," in Graphics Gems, A. Glassner, ed., Academic Press, Boston, 1991.

Ning Liu, Houzhi Jin, Alyn P. Rockwood, "Antialiasing by Gaussian Integration," IEEE Computer Graphics and Applications, vol. 16, no. 3, pp. 58-63, May 1996, doi:10.1109/38.491186
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