Fast detection of periodic signals in image sequences

Gennady Feldman; Doron Bar; Israel Tugendhaft

doi:10.1117/12.485750

25 August 2003 Fast detection of periodic signals in image sequences

Gennady Feldman, Doron Bar, Israel Tugendhaft

Proceedings Volume 5096, Signal Processing, Sensor Fusion, and Target Recognition XII; (2003) https://doi.org/10.1117/12.485750
Event: AeroSense 2003, 2003, Orlando, Florida, United States

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.

Citation Download Citation

Gennady Feldman, Doron Bar, and Israel Tugendhaft "Fast detection of periodic signals in image sequences", Proc. SPIE 5096, Signal Processing, Sensor Fusion, and Target Recognition XII, (25 August 2003); https://doi.org/10.1117/12.485750

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