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Optimized Kaiser-Bessel Window Functions for Computed Tomography

M. Nilchian, J.P. Ward, C. Vonesch, M. Unser

IEEE Transactions on Image Processing, vol. 24, no. 11, pp. 3826-3833, November 2015.

Kaiser-Bessel window functions are frequently used to discretize tomographic problems because they have two desirable properties: 1) their short support leads to a low computational cost and 2) their rotational symmetry makes their imaging transform independent of the direction. In this paper, we aim at optimizing the parameters of these basis functions. We present a formalism based on the theory of approximation and point out the importance of the partition-of-unity condition. While we prove that, for compact-support functions, this condition is incompatible with isotropy, we show that minimizing the deviation from the partition of unity condition is highly beneficial. The numerical results confirm that the proposed tuning of the Kaiser-Bessel window functions yields the best performance.

AUTHOR="Nilchian, M. and Ward, J.P. and Vonesch, C. and Unser, M.",
TITLE="Optimized {K}aiser-{B}essel Window Functions for Computed
JOURNAL="{IEEE} Transactions on Image Processing",

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