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Wavelet packet decomposition 2-D
wpdec2 is a two-dimensional wavelet packet analysis function.
T = wpdec2(X,N,'wname',E,P) returns a wavelet packet tree T corresponding to the wavelet packet decomposition of the matrix X, at level N, with a particular wavelet ('wname', see wfilters for more information).
T = wpdec2(X,N,'wname') is equivalent to T = wpdec2(X,N,'wname','shannon').
E is a string containing the type of entropy and P is an optional parameter depending on the value of T (see wentropy for more information).
See wpdec for a more complete description of the wavelet packet decomposition.
When X represents an indexed image, X is an m-by-n matrix. When X represents a truecolor image, it is an m-by-n-by-3 array, where each m-by-n matrix represents a red, green, or blue color plane concatenated along the third dimension.
For more information on image formats, see the image and imfinfo reference pages.
% The current extension mode is zero-padding (see dwtmode). % Load image. load tire % X contains the loaded image. % For an image the decomposition is performed using: t = wpdec2(X,2,'db1'); % The default entropy is shannon. % Plot wavelet packet tree % (quarternary tree, or tree of order 4). plot(t)
The algorithm used for the wavelet packets decomposition follows the same line as the wavelet decomposition process (see dwt2 and wavedec2 for more information).
Coifman, R.R.; M.V. Wickerhauser (1992), "Entropy-based algorithms for best basis selection," IEEE Trans. on Inf. Theory, vol. 38, 2, pp. 713-718.
Meyer, Y. (1993), Les ondelettes. Algorithmes et applications, Colin Ed., Paris, 2nd edition. (English translation: Wavelets: Algorithms and Applications, SIAM).
Wickerhauser, M.V. (1991), "INRIA lectures on wavelet packet algorithms," Proceedings ondelettes et paquets d'ondes, 17-21 June, Rocquencourt, France, pp. 31-99.
Wickerhauser, M.V. (1994), Adapted wavelet analysis from theory to software Algorithms, A.K. Peters.
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