Information AboutDecorrelation |
| CATEGORIES ABOUT DECORRELATION | |
| signal processing | |
| image processing | |
| computational physics | |
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Although most decorrelation algorithms are linear, non-linear decorrelation algorithms also exist. Many data compression algorithms incorporate a decorrelation stage. For example, many Transform Coder s first apply a fixed linear transformation that would, on average, have the effect of decorrelating a typical signal of the class to be coded, prior to any later processing. This is typically a Karhunen-Loève Transform , or a simplified approximation such as the Discrete Cosine Transform . By comparison, Sub-band Coder s do not generally have an explicit decorrelation step, but instead exploit the already-existing reduced correlation within each of the sub-bands of the signal, due to the relative flatness of each sub-band of the power spectrum in many classes of signals. Linear Predictive Coder s can be modeled as an attempt to decorrelate signals by subtracting the best possible linear prediction from the input signal, leaving a whitened residual signal. Decorrelation techniques can also be used for many other purposes, such as reducing Crosstalk in a multi-channel signal, or in the design of Echo Canceller s. In Image Processing decorrelation techniques can be used to enhance or Stretch , Colour differences found in each Pixel of an image. This is generally termed as 'decorrelation stretching'. The concept of decorrelation can be applied in many other fields, including Neuroscience , where it can be used in the analysis of the Neural Network s in the human visual system, and in Cryptography (see Decorrelation Theory ). SEE ALSO EXTERNAL LINKS
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