A fast image reconstruction algorithm using significant sample point selection and linear bivariate splines

Author

Verma, Rohit ; Srivastava, Gaurav Kumar ; Mahrishi, Ruchika ; Rajesh, Siddavatam

Author_Institution

Comput. Sci., Jaypee Univ. of Inf. Technol., Solan, India

fYear

2009

fDate

23-26 Jan. 2009

Firstpage

1

Lastpage

6

Abstract

The image reconstruction using linear bivariate splines and Delaunay triangulation is addressed in this paper. A novel significant sample point selection is used to get the most significant samples for triangulation. Image reconstruction is done based on the approximation of image regarded as a function, by a linear spline over adapted Delaunay triangulation. The proposed method is compared with some of the existing image reconstruction spline models.

Keywords

image processing; mesh generation; splines (mathematics); Delaunay triangulation; fast image reconstruction algorithm; image regarded approximation; linear bivariate splines; significant sample point selection; Computer science; Filter bank; Gray-scale; Image edge detection; Image reconstruction; Image sampling; Information technology; Reconstruction algorithms; Scattering; Spline; delaunay triangulation; image processing; linear Bivariate splines;

fLanguage

English

Publisher

ieee

Conference_Titel

TENCON 2009 - 2009 IEEE Region 10 Conference

Conference_Location

Singapore

Print_ISBN

978-1-4244-4546-2

Electronic_ISBN

978-1-4244-4547-9

Type

conf

DOI

10.1109/TENCON.2009.5396243

Filename

5396243