functions that perform two-dimensional discrete wavelet transform (DWT).
In many applications the multiresolution analysis by
discrete wavelet transforms is a better alternative to windowing and discrete
Fourier analysis techniques. On the one hand, the forward two-dimensional
wavelet transform may be considered as a decomposition of an image on the base
of functions bounded or localized in space; and on the other, the wavelet
transforms are related to subband filtering and resampling.
Intel IPP for image processing contains one-level
discrete wavelet decomposition and reconstruction functions. It also provides
the necessary interface for initialization and deallocation of the transform
The wavelet transform type can be set by specifying
the appropriate filter taps in the initialization function.
Note that Intel IPP supports only one-dimensional
finite impulse response filters for separable convolution.
The Intel IPP functions for wavelet decomposition and
reconstruction use fast polyphase algorithm, which is equivalent to traditional
application of separable convolution and dyadic resampling in different order.
shows the equivalent algorithm of wavelet reconstruction
of an image.
Wavelet transform functions support regions of
interest (ROI, see
Regions of Interest in Intel IPP) in the images. However, these functions do not perform
internally any border extensions of image ROI data. It means that source images
must already contain all border data that are necessary for convolution
operations. See descriptions of the functions
information on how to calculate extended image border sizes.