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Proceedings Paper

Extension of Rader's algorithm for high-speed multidimensional autocorrelation
Author(s): R. Rinaldo; Riccardo Bernardini; Guido Maria Cortelazzo
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Paper Abstract

The computation of an estimate of the autocorrelation function from available data enters a great number of signal processing applications and typically represents the bulk of the computation time required in each application. This work investigates frequency domain techniques for the evaluation of the autocorrelation of multidimensional signals: in particular, the extension of Rader's algorithm for 1D signals is considered. The bidimensional case is treated in detail because it is of special interest for applications and because the reasoning used can be readily applied to higher dimension signals. The direct extension of Rader's algorithm to the multidimensional case is not optimal with respect to the choice of the subblock dimension, unlike in the one dimensional case: a modified algorithm is proposed that allows further computational savings and is particularly attractive for the data organization. The computation time required by frequency domain techniques is evaluated in detail. The analysis confirms that the proposed frequency domain techniques lead to significant computation time savings.

Paper Details

Date Published: 1 November 1991
PDF: 15 pages
Proc. SPIE 1606, Visual Communications and Image Processing '91: Image Processing, (1 November 1991); doi: 10.1117/12.50336
Show Author Affiliations
R. Rinaldo, Univ. di Padova (Italy)
Riccardo Bernardini, Univ. di Padova (Italy)
Guido Maria Cortelazzo, Univ. di Padova (Italy)


Published in SPIE Proceedings Vol. 1606:
Visual Communications and Image Processing '91: Image Processing
Kou-Hu Tzou; Toshio Koga, Editor(s)

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