wavDTWT.2d( x, n.levels = 3, biorthogonal = ``nearsyma", qshift = ``a" )
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(3) N. G. Kingsbury, ``A dual-tree complex wavelet transform with improved orthogonality and symmetry properties'', Proc. IEEE Conf. on Image Processing, Vancouver, Sept. 11-13, 2000, Paper 1429.
(4) I. Daubechies, ``Orthonormal Bases of Compactly Supported Wavelets'', Communications on Pure and, Applied Mathematics, 41, 909-96.
## create an image img <- make.image("flower", 128) ## calculate DTWT coefficients of an image x.img ## through level 3 y <- wavDTWT.2d(img, n.levels = 3, bior = "nearsymb", + qshift = "b", title.data = "Flower" ) ## display results print(y) ## plot complex magnitudes (decibels) of wavelet ## coefficients for all six angular orientations ## at level 1 plot(y, level=1) ## same plot, but showing actual magnitudes, not decibels plot(y, decibels=F, level = 1) ## same plot, but with all magnitudes less than 60 ## percent of maximum values set to zero plot(y, decibels=F, level = 1, threshold=0.60) ## same type of plot, but showing an enlarged view of ## only the +15 deg plot plot(y, decibels=F, level = 1, angle=15, threshold=0.60) ## same as above, but showing both the +15 deg and ## -15 deg plots plot(y, decibels=F, level = 1, angle=c(15,-15), + threshold=0.60) ## reconstruct image from its 2D DTWT img.recon <- reconstruct(y) ## verify reconstruction vecnorm(img.recon - img)/vecnorm(img)