Perturbing Bézier coefficients for best constrained degree reduction in the L2-norm

  • Authors:
  • Jianmin Zheng;Guozhao Wang

  • Affiliations:
  • Department of Computer Science, Brigham Young University, Provo, UT;Department of Mathematics/Institute of Image and Computer Graphics, Zhejiang University, Hangzhou 310027, PR China

  • Venue:
  • Graphical Models
  • Year:
  • 2003

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Abstract

This paper first shows how the Bézier coefficients of a given degree n polynomial are perturbed so that it can be reduced to a degree m ( n) polynomial with the constraint that continuity of a prescribed order is preserved at the two endpoints. The perturbation vector, which consists of the perturbation coefficients, is determined by minimizing a weighted Euclidean norm. The optimal degree n - 1 approximation polynomial is explicitly given in Bézier form. Next the paper proves that the problem of finding a best L2-approximation over the interval [0, 1] for constrained degree reduction is equivalent to that of finding a minimum perturbation vector in a certain weighted Euclidean norm. The relevant weights are derived. This result is applied to computing the optimal constrained degree reduction of parametric Bézier curves in the L2-norm.