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Proceedings Paper

Local cardinal spline interpolation and its application to image processing
Author(s): Andrew K. Chan; Charles K. Chui; Jun Zha; Q. Liu
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Paper Abstract

This paper presents an image interpolation algorithm using the recently developed local cardinal interpolatory spline (LCIS). The procedures for constructing the LCIS basis are described for both univariate and bivariate cases. This new LCIS algorithm is very efficient and can be implemented easily. Without the need of a mapping procedure, this method is faster than any other polynomial interpolation approach. The C2 property of the LCIS also allows the gradient operator to be constructed for edge detection. Both image interpolation and edge detection algorithms are compared with existing methods in two different examples.

Paper Details

Date Published: 1 February 1992
PDF: 12 pages
Proc. SPIE 1610, Curves and Surfaces in Computer Vision and Graphics II, (1 February 1992); doi: 10.1117/12.135151
Show Author Affiliations
Andrew K. Chan, Texas A&M Univ. (United States)
Charles K. Chui, Texas A&M Univ. (United States)
Jun Zha, Texas A&M Univ. (United States)
Q. Liu, Texas A&M Univ. (United States)


Published in SPIE Proceedings Vol. 1610:
Curves and Surfaces in Computer Vision and Graphics II
Martine J. Silbermann; Hemant D. Tagare, Editor(s)

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