Discrete transform
 | This article or section is in a state of significant expansion or restructuring. You are welcome to assist in its construction by editing it as well. If this article or section has not been edited in several days, please remove this template. If you are the editor who added this template and you are actively editing, please be sure to replace this template with {{in use}} during the active editing session. Click on the link for template parameters to use.
This article was last edited by Dicklyon (talk | contribs) 14 years ago. (Update timer) |
In signal processing, discrete transforms are mathematical transforms, often linear transforms, of signals between discrete domains, such as between discrete time and discrete frequency.[1]
Mant common integral transforms used in signal processing have their discrete counterparts. For example, for the Fourier transform the counterpart is the discrete Fourier transform.
In addition to spectral analysis of signals, discrete transforms play important role in data compression, signal detection, digital filtering and correlation analysis.[2]
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 to continuous frequency, and the Fourier series, from continuous time to discrete frequency, are outside the class of discrete transforms.
Classical signal processing deals with one-dimensional discrete transforms. Other application areas, such as image processing, computer vision, high definition television, visual telephony, etc. make use of two-dimensional and in general, multidimensional discrete transforms.
See also
References
- ^ Jerry C. Whitaker (2001). Television receivers. McGraw-Hill Professional. p. 147. ISBN 9780071380423.
- ^ Graham Wade (1994). Signal coding and processing (2nd ed.). Cambridge University Press. p. 332. ISBN 9780521423366.