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