1 July 1994 Two fast approximate wavelet algorithms for image processing, classification, and recognition
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Optical Engineering, 33(7), (1994). doi:10.1117/12.172905
Abstract
We use large libraries of template waveforms with remarkable orthogonality properties to recast the relatively complex principal orthogonal decomposition (POD) into an optimization problem with a fast solution algorithm. Then it becomes practical to use POD to solve two related problems: recognizing or classifying images, and inverting a complicated map from a low-dimensional configuration space to a highdimensional measurement space. In the case where the number N of pixels or measurements is more than 1000 or so, the classical O(N3) POD algorithm becomes very costly, but it can be replaced with an approximate best-basis method that has complexity O(N2 logN). A variation of POD can also be used to compute an approximate Jacobian for the complicated map.
Mladen Victor Wickerhauser, "Two fast approximate wavelet algorithms for image processing, classification, and recognition," Optical Engineering 33(7), (1 July 1994). http://dx.doi.org/10.1117/12.172905
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KEYWORDS
Wavelets

Argon

Bromine

Detection and tracking algorithms

Image processing

Condition numbers

Image classification

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