Directional Splines and Their Use for Smoothing Ejections and Fractures of Interpolant

Authors

  • Vladimir A. Kodnyanko Сибирский федеральный университет

DOI:

https://doi.org/10.14529/cmse210101

Keywords:

spline, Schoenberg spline, Akima spline, directional spline

Abstract

A method for constructing a directional cubic spline for a set of points on a plane is formulated and proposed. The spline is compared with the Schoenberg B-spline, Akima and Catmull–Rom splines. It is shown that for unequally spaced points, in comparison with the B-spline, it gives significantly lower overshoots and is practically free of strong kinks, which are characteristic of Akima splines. The spline does not give loops and oscillations, which are a characteristic drawback of parametric splines, in particular, Hermitian ones, which include the Catmull–Rom spline. A fast method for optimizing the spline guiding coefficient is proposed, the purpose of which is to minimize the discontinuities of the second derivative of the function at its intermediate points. An example of optimization of a directional third-order spline is given. A fourth-order directional spline, which is free of kinks, is also proposed. The method of optimization of the directional spline of the fourth order is formulated, the algorithm of its optimization is stated. The optimization criteria are the spline length and the smallest distance between its global maximum and minimum. It is shown that, in comparison with the Schoenberg spline, the fourth-order directional spline has smaller outliers. A method for automatic blunting of sharp peaks of curves is proposed, which can be applied to all types of splines.

Author Biography

Vladimir A. Kodnyanko, Сибирский федеральный университет

Кафедра стандартизации и управления качеством СФУ, профессор

References

Powell M.J.D. Approximation Theory and Methods. Cambridge University Press, 1981. 352 p. DOI: 10.1017/CBO9781139171502.

Atkinson K.A. An Introduction to Numerical Analysis (2nd ed.). John Wiley and Sons, 1988. 615 p.

Watson G.A. Approximation Theory and Numerical Methods. John Wiley, 1980. 229 p.

Schatzman M. Numerical Analysis: A Mathematical Introduction. Clarendon Press, 2002. 496 p.

Schoenberg I.J. Contributions to the problem of approximation of equidistant data by analytic functions. Quart. Appl. Math. 1946. Vol. 4. P. 45–99, 112–141.

Ahlberg J.H., Nilson E.N., Walsh J.L. The Theory of Splines and Their Application. Academic Press, 1967. 296 p.

David F., Rogers J., Adams A. Mathematical Elements for Computer Graphics. McGraw-Hill Science / Engineering / Math, 2 edition, 1989. 611 p.

Cohen D. Incremental Methods for Computer Graphics. PhD Thesis. Harvard University, 1969.

Warnock J.E. A Hidden Surface Algorithm for Computer-Generated Halftone Pictures. Computer Science Department, University of Utah, TR 1–15. 1969.

Watkins G.S. A Real-Time Visible Surface Algorithm. Computer Science Department, University of Utah, UTECH-CSC-70-101, 1970.

Akima H. A New Method of Interpolation and Smooth Curve Fitting Based on Local Procedures. Journal of the ACM. 1970. Vol. 17, no. 4. P. 589–602. DOI: 10.1145/321607.321609.

Catmull E., Rom R. A class of local interpolating splines. Computer Aided Geometric Design. 1974. P. 317–326.

Barry P.J., Goldman R.N. Recursive evaluation algorithm for a class of Catmull-Rom splines. Computer Graphics. 1988. Vol. 22, no. 4. P. 199–204. DOI: 10.1145/378456.378511.

Kiefer J.K. Sequential minimax search for a maximum. P. Am. Math. Soc. 1953. P. 502–506.

Brent R.P. Algorithms for Minimization without Derivatives. Dover, 2002. 195 p.

Krukovets A.S., Gorelkin G.A. Development of a method for interpolating the values of the nomogram. Modern scientific research and innovations. 2015. No. 5(2). URL: http://web.snauka.ru/issues/2015/05/53846 (accessed: 14.06.2020) (in Russian)

Dobson A.J. An Introduction to Statistical Modelling. Chapman and Hall, London, 1983.

Kodnyanko V.A. On computational redundancy of the dichotomous search and conditional minimization of unimodal functions by the economical dichotomous search. Systems and means of informatics. 2019. Vol. 29, no. 1. P. 164–173. DOI: 10.14357/08696527190113 (in Russian)

Ruckdeschel F.R. Basic scientific subroutines. Vol. 2. BYTE/McGRAW-HILL, 1981.

Yanenko N.N., Kvasov B.I. An Iterative Method for Constructing Polycubic Spline Functions. Dokl. USSR Academy of Sciences. 1970. Vol. 195, no. 5. P. 1055–1057. (in Russian)

Constantini P., Morandi R. An algorithm for computing shape-preserving cubic spline interpolation to data. Calcolo. 1984. Vol. 21. P. 295–305.

Ryabenky V.S. Local formulas for smooth completion and smooth interpolation of functions by their values at nodes of an uneven rectangular grid. Preprint, Inst. mathematics of the Academy of Sciences of the USSR. IPM. 1974. No. 21. (in Russian)

Dietze S., Schmidt J.W. Determination of shape preserving spline interpolants with minimal curvature via dual programs. J. Approxim. Theory. 1988. Vol. 52, no. 1. P. 43–57.

Zavyalov Yu.S., Kvasov B.I., Miroshnichenko V.L. Methods of spline functions. Moscow, Nauka, 1980. (in Russian)

Miroshnichenko V.L. Isogeometric properties and approximation error for weighted cubic splines. Computing Systems. Novosibirsk: IM SB RAS, 1995. Vol. 154. P. 127–154. (in Russian)

Korneychuk N.P., Babenko V.F., Ligun A.A. Extreme properties of polynomials and splines. Kiev, Naukova Dumka, 1992. 304 p. (in Russian)

Dzyubenko G.A., Gilewicz J., Shevchuk I. A. New phenomena in coconvex approximation. Analysis Mathematica. 2006. Vol. 32, no. 2. P. 113–121. DOI: 10.1007/s10476-006-0005-x.

Stechkin S.B., Subbotin Yu.N. Splines in computational mathematics. Moscow, Nauka, 1976. 248 p. (in Russian)

Volkov Yu.S. A new method for constructing interpolation cubic splines. Computational Mathematics and Mathematical Physics. 2004. Vol. 44, no. 2. P. 231–241. (in Russian)

Kodnyanko V.A. Video DS4-spline optimization 1. URL: http://smiuk.sfu-kras.ru/kodnyanko/site/science/Video1.mp4 (accessed: 12.07.2020).

Kodnyanko V.A. Video DS4-spline optimization 2. URL: http://smiuk.sfu-kras.ru/kodnyanko/site/science/Video2.mp4 (accessed: 12.07.2020).

Kodnyanko V.A. Video DS4-spline optimization 3. URL: http://smiuk.sfu-kras.ru/kodnyanko/site/science/Video3.mp4 (accessed: 12.07.2020).

Published

2021-02-10

Issue

Section

Numerical Mathematics