DocumentCode :
2647584
Title :
Optimal parameter choice for a class of cubic interpolation kernels and the associated error analysis
Author :
Aggarwal, Manoj ; Gadre, Vikram
Author_Institution :
Beckman Inst. for Adv. Sci. & Technol., Illinois Univ., Urbana, IL, USA
Volume :
3
fYear :
1996
fDate :
16-19 Sep 1996
Firstpage :
723
Abstract :
Two issues related to a class of cubic kernels for interpolation with a single free parameter are addressed in this paper. The first issue relates to parametrizing the cubic interpolation kernel optimally for arbitrary kernel length keeping in view the need to cancel all error terms up to the second order. This builds upon the results of Keys (1981) where the optimal parameter value is obtained only for a kernel length of 2. The second issue relates to obtaining a precise mathematical formulation for the advantage gained in increasing the kernel length. The associated third order error analysis shows that the error coefficients decrease monotonically in magnitude with an increase in the kernel length. Asymptotic results are also obtained for the spline length tending to infinity
Keywords :
error analysis; image processing; interpolation; splines (mathematics); asymptotic results; cubic interpolation kernels; error analysis; error coefficients; error terms; images; kernel length; mathematical formulation; optimal parameter choice; optimal parameter value; parameterization; spline length; third order error analysis; Closed-form solution; Error analysis; H infinity control; Image processing; Interpolation; Kernel; Satellites; Signal processing; Spline; Taylor series;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing, 1996. Proceedings., International Conference on
Conference_Location :
Lausanne
Print_ISBN :
0-7803-3259-8
Type :
conf
DOI :
10.1109/ICIP.1996.560787
Filename :
560787
Link To Document :
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