Summary
The detection of local regular patterns and dependent values in heavy noised signal is proposed in this paper. The moving window approach allows computation of the maximal autocovariance of signal. The differences are emphasized using Spatio–Temporal Track–Before–Detect algorithm so tracking such objects is possible. The possibilities of this technique are shown in a few illustrative examples and discussed. The detection of weak signals hidden in the background noise is emphasized.
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Mazurek, P. (2014). Preprocessing Using Maximal Autocovariance for Spatio–Temporal Track–Before–Detect Algorithm. In: S. Choras, R. (eds) Image Processing and Communications Challenges 5. Advances in Intelligent Systems and Computing, vol 233. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-01622-1_6
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DOI: https://doi.org/10.1007/978-3-319-01622-1_6
Publisher Name: Springer, Heidelberg
Print ISBN: 978-3-319-01621-4
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