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A discrete cosine transform (DCT) expresses a finite sequence of data points in terms of a sum of cosine functions oscillating at different frequencies. The DCT, first proposed by Nasir Ahmed in 1972, is a widely used transformation technique in signal processing and data compression .
The discrete cosine transform (DCT) is the most widely used transform coding compression algorithm in digital media, followed by the discrete wavelet transform (DWT). Transforms between a discrete domain and a continuous domain are not discrete transforms. For example, the discrete-time Fourier transform and the Z-transform, from discrete time ...
The sine-only expansion for equally spaced points, corresponding to odd symmetry, was solved by Joseph Louis Lagrange in 1762, for which the solution is a discrete sine transform. The full cosine and sine interpolating polynomial, which gives rise to the DFT, was solved by Carl Friedrich Gauss in unpublished work around 1805, at which point he ...
Binomial transform; Discrete Fourier transform, DFT Fast Fourier transform, a popular implementation of the DFT; Discrete cosine transform. Modified discrete cosine transform; Discrete Hartley transform; Discrete sine transform; Discrete wavelet transform; Hadamard transform (or, Walsh–Hadamard transform) Fast wavelet transform
Thus, the specific case of = = / is known as an odd-time odd-frequency discrete Fourier transform (or O 2 DFT). Such shifted transforms are most often used for symmetric data, to represent different boundary symmetries, and for real-symmetric data they correspond to different forms of the discrete cosine and sine transforms.
The most widely used transform coding technique in this regard is the discrete cosine transform (DCT), [1] [2] proposed by Nasir Ahmed in 1972, [3] [4] and presented by Ahmed with T. Natarajan and K. R. Rao in 1974. [5] This DCT, in the context of the family of discrete cosine transforms, is the DCT-II.
The 2D Z-transform, similar to the Z-transform, is used in multidimensional signal processing to relate a two-dimensional discrete-time signal to the complex frequency domain in which the 2D surface in 4D space that the Fourier transform lies on is known as the unit surface or unit bicircle.
For example, one can use the coordinate remapping = (/), where L is a user-specified constant (one could simply use L=1; an optimal choice of L can speed convergence, but is problem-dependent [11]), to transform the semi-infinite integral into: