Optimal approximation-interpolation sampling systems: relation to wavelets and image coding

Ajit S. Bopardikar; Raghuveer M. Rao

doi:10.1117/12.342952

22 March 1999 Optimal approximation-interpolation sampling systems: relation to wavelets and image coding

Proceedings Volume 3723, Wavelet Applications VI; (1999) https://doi.org/10.1117/12.342952
Event: AeroSense '99, 1999, Orlando, FL, United States

Abstract

In this paper, we present closed form expressions for filters in multidimensional interpolation and approximation sampling systems matched to the input random field or image class in the mean squared sense. We then present expression for the mean squared error between the reconstructed and the input field. For the approximation sampling system we use this expression to show that the optimal antialiasing and reconstruction filters are spectral factors or an ideal brickwall-type of a filter. Finally, we give examples of filters matched to an image class generated using a spearable AR model and a quincunx sampling lattice and compare their performance with that of some standard interpolators.

Citation Download Citation

Ajit S. Bopardikar and Raghuveer M. Rao "Optimal approximation-interpolation sampling systems: relation to wavelets and image coding", Proc. SPIE 3723, Wavelet Applications VI, (22 March 1999); https://doi.org/10.1117/12.342952

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