Discrete Cosine Transform

By S. Weiss. 1996

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Citations in the corpus

Scale-Dependence of the Predictability of Precipitation from Continental Radar Images. Part I: Description of the Methodology (2002, methodology): “The images are decomposed by means of a low-pass filter in the spectral domain using discrete-cosine-transforms (DCT; Ahmed et al. 1974; Gonzalez and Woods 1992).”
Spectral Decomposition of Two-Dimensional Atmospheric Fields on Limited-Area Domains Using the Discrete Cosine Transform (DCT) (2002, background): “It can be shown that this procedure leads to a special Fourier transform called the discrete cosine transform, first introduced by Ahmed et al. (1974) for digital image processing purposes.”
Hyperspectral and Multispectral Image Fusion Based on a Sparse Representation (2014, background): “ proposed as a basis for the image patches. In many applications, the dictionary D is predeﬁned and can be constructed from wavelets [47], curv elets 7 [48] or discrete cosine transform (DCT) vectors [49]. However, these bases are not necessarily well matched to natural or remote sensing images sinc”
A generalized grid connectivity–based parameterization for subsurface flow model calibration (2011, methodology): “For the DCT, maximal compression power results from its asymptotic convergence to PCA of a first‐order stationary Markov process [Ahmed et al., 1974].”
React Scatterplot Smoothers: Superefficiency through Basis Economy (2000, methodology): “a modification of the discrete Fourier transform (double the range and reflect about an endpoint) that avoids creating Gibbs phenomena at the beginning and end of the REACT estimator of η. Rao and Yip (1990) discussed properties, algorithms and applications of the discrete cosine transform to digi”
Sparse Modeling for Image and Vision Processing (2014, methodology): “The components resemble Fourier basis—that is, product of sinusoids with different frequencies and phases, similarly to the discrete cosine transform (DCT) dictionary [Ahmed et al., 1974] presented in Figure 2.4(a).”
Design, analysis and experimental evaluation of block based transformation in MFCC computation for speaker recognition (2012, methodology): “Firstly, the DCT is the sub-optimal approximation of the basis function of Karhunen– Loéve transform (KLT) when the correlation matrix of the sample closely approximates the correlation matrix of Markov-I process (Ahmed et al., 1974).”