Wavelets and Subband Coding

By Martin Vetterli, Jelena Kovacevic. Prentice Hall Signal Processing Series, 2013

3,011 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/5216ea733e562541b33a7f97dab0de072b2e8827

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Citations in the corpus

Compression of multispectral images by three-dimensional SPIHT algorithm (2000, unknown): “In the transform coding framework, wavelet transform [11], [ 12 ] deserves a special treatment because of its peculiar characteristics.”
Curvelets: A Surprisingly Effective Nonadaptive Representation for Objects with Edges (2000, background): “The construction of such operators is standard [15]; the coronization oriented around powers 2 is nonstandard – and essential for us.”
Object Detection Using the Statistics of Parts (2004, unknown): “Several books describe their design (Strang and Nguyen, 1997; Vetterli and Kovacevic, 1995).”
A Kaiser window approach for the design of prototype filters of cosine modulated filterbanks (1998, unknown): “397, [6]).”
Sampling-50 years after Shannon (2000, background): “The reader who wishes to learn more about wavelets is referred to the standard texts [35], [79], [115], [ 139 ].”
New multiscale transforms, minimum total variation synthesis: applications to edge-preserving image reconstruction (2002, background): “The last section introduced ridgelets and we first briefly discuss multiscale ridgelets and bandpass filtering.”
Sparse Recovery of Streaming Signals Using $\ell_1$-Homotopy (2013, background): “to overlapping, compact intervals is the wavelet transform. A wavelet transform decomposes a signal into orthogonal components with overlapping supports at different resolutions in time and frequency [23,46]. The scaling and wavelet functions used for this purpose overlap one another while maintaini”
Foundations of Signal Processing (2014, background): “1 Musical score as an illustration of a time–frequency plane [107].”
Combined DWT-DCT Digital Image Watermarking (2007, methodology): “However, DWT [7] has been used in digital image watermarking more frequently due to its excellent spatial localization and multi-resolution characteristics, which are similar to the theoretical models of the human visual system [8] .”
Walk detection and step counting on unconstrained smartphones (2013, methodology): “The short-term Fourier transform (STFT) [55] can be applied to evaluate the frequency content of successive windows of data [5].”
Multiple description coding: compression meets the network (2001, background): “... data is sent on Channel 1 (thus to all users in a broadcast or first in sequence) and additional data to improve the reconstruction quality is sent on Channel 2. For example, most significant bits can be sent on Channel 1 and least significant on Channel 2. For images, a coarse or low pass versi”
Wavelet-based texture retrieval using generalized Gaussian density and Kullback-Leibler distance (2002, methodology): “Fast implementation of DWF is obtained via the \algorithme a trous" where each decomposition step involves a convolution with the basic lter H0 and H1, which are expanded by insertion of an appropriate number of zeros between taps, and skips the downsampling [25].”
Directional multiscale modeling of images using the contourlet transform (2006, methodology): “Images have effectively been modeled using the wavelet transform [ 1 ], [2], which offers a multiscale and time-frequency-localized image representation.”
Sampling signals with finite rate of innovation (2002, background): “Clearly, the rate of innovation is . There are many examples of such signals, for example, when is a scaling function in a wavelet multiresolution framework [8], [ 20 ] and in approximation theory [17].”