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Proceedings Paper

Fast detection of periodic signals in image sequences
Author(s): Gennady Feldman; Doron Bar; Israel Tugendhaft
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Paper Abstract

The article describes a new, improved and fast version of our method and algorithm1 for detection of periodic signals in image sequences, i.e. signals that appear in a small number of adjacent pixels of an image sequence and are periodic in the temporal domain. The signal information is accumulated from adjacent pixels with the spectrum-specific version of Principal Components1. For this uniformly-sampled accumulated signal, a model dependent on few parameters is used for signal fitting. In this new version: 1) the sampling frequency may be below the Nyquist rate, and the model includes fold-over frequencies as well. 2) The general linear LS fit with pre-computed inverse matrixes was used for the model parameter estimation. It speeds-up the procedure. 3) The procedure is also speeded-up by preliminary pixel selection based on coarse estimation of the signal energy and SNR by the cross-power spectrum (CPS) method ith small data sub-frames. Our spectrum-specific covariance matrix estimate, employed in Spectrum-Specific Principal Components, is made more robust by utilizing the CPS method with small data sub-frames. The algorithm was tested by processing simulated image sequences as well as some real ones.

Paper Details

Date Published: 25 August 2003
PDF: 8 pages
Proc. SPIE 5096, Signal Processing, Sensor Fusion, and Target Recognition XII, (25 August 2003); doi: 10.1117/12.485750
Show Author Affiliations
Gennady Feldman, Soreq Nuclear Research Ctr. (Israel)
Doron Bar, Soreq Nuclear Research Ctr. (Israel)
Israel Tugendhaft, Soreq Nuclear Research Ctr. (Israel)

Published in SPIE Proceedings Vol. 5096:
Signal Processing, Sensor Fusion, and Target Recognition XII
Ivan Kadar, Editor(s)

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