Volume XLII-4/W18
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W18, 343–348, 2019
https://doi.org/10.5194/isprs-archives-XLII-4-W18-343-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W18, 343–348, 2019
https://doi.org/10.5194/isprs-archives-XLII-4-W18-343-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

  18 Oct 2019

18 Oct 2019

APPLICATION OF B-SPLINE METHOD IN SURFACE FITTING PROBLEM

F. Esmaeili, A. Amiri-Simkooei, V. Nafisi, and A. Alizadeh Naeini F. Esmaeili et al.
  • Department of Geomatics Engineering, Faculty of Civil Engineering and Transportation, University of Isfahan, Isfahan, Iran

Keywords: least-squares approximation, B-spline functions, surface fitting, splines’ basis functions, 2D data analysis, continuity constrains

Abstract. Fitting a smooth surface on irregular data is a problem in many applications of data analysis. Spline polynomials in different orders have been used for interpolation and approximation in one or two-dimensional space in many researches. These polynomials can be made by different degrees and they have continuous derivative at the boundaries. The advantage of using B-spline basis functions for obtaining spline polynomials is that they impose the continuity constraints in an implicit form and, more importantly, their calculation is much simpler. In this study, we explain the theory of the least squares B-spline method in surface approximation. Furthermore, we present numerical examples to show the efficiency of the method in linear, quadratic and cubic forms and it’s capability in modeling changes in numerical values. This capability can be used in different applications to represent any natural phenomenon which can’t be experienced by humans directly. Lastly, the method’s accuracy and reliability in different orders will be discussed.