Abstract
We use the eigenvalues of a version of the autocovariance matrix to recognize directions at which the Fourier transform of a function is slowly decreasing, which provides us with a technique to detect singularities in images. In very high dimensions, we show how the wavelet packet best-basis algorithm can be used to compute these eigenvalues approximately, at relatively low computational complexity.
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© 2001 Springer-Verlag Berlin Heidelberg
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Wickerhauser, M.V. (2001). Singularity Detection from Autocovariance via Wavelet Packets. In: Tang, Y.Y., Yuen, P.C., Li, Ch., Wickerhauser, V. (eds) Wavelet Analysis and Its Applications. WAA 2001. Lecture Notes in Computer Science, vol 2251. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45333-4_3
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DOI: https://doi.org/10.1007/3-540-45333-4_3
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Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-43034-6
Online ISBN: 978-3-540-45333-8
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