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The '''triple correlation''' of an ordinary function on the real line is the integral of the
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product of that function with two independently shifted copies of itself:
 
<math>
 
\int_{-\infty}^{\infty} f^{*}(x) f(x+s_1) f(x+s_2) dx
 
</math>
 
The Fourier transform of triple correlation is the [[bispectrum]]. The triple correlation extends  the concept of [[autocorrelation]], which correlates a function with a single shifted copy of itself and thereby enhances its latent periodicities.
 
== History ==
 
The theory of the triple correlation was first investigated by statisticians examining the [[cumulant]] structure of non-gaussian random processes. It was also independently studied by physicists as a tool for [[spectroscopy]] of laser beams. H. Gamo in 1963 described an apparatus for measuring the triple correlation of a laser beam, and also showed how phase information can be recovered from the real part of the bispectrum---up to sign reversal and linear offset.  However, Gamo's method implicitly requires the Fourier transform to never be zero at any frequency.  This requirement was relaxed, and the class of functions which are known to be uniquely identified by their triple (and higher-order) correlations was considerably expanded, by the study of Yellott and Iverson (1992).  Yellott & Iverson also pointed out the connection between triple correlations and the visual texture discrimination theory proposed by [[Bela Julesz]].
 
== Applications ==
 
Triple correlation methods are frequently used in signal processing for treating signals
that are corrupted by [[additive white Gaussian noise]]; in particular, triple correlation
techniques are suitable when multiple observations of the signal are available
and the signal may be translating in between the observations, e.g.,a sequence of
images of an object translating on a noisy background. What makes the triple
correlation particularly useful for such tasks are three properties: (1) it is
invariant under translation of the underlying signal; (2) it is unbiased in
additive Gaussian noise; and (3) it retains nearly all of the relevant phase information in the
underlying signal. Properties (1)-(3) of the triple correlation extend in many cases to
functions on an arbitrary [[locally compact group]], in particular to the groups of
rotations and rigid motions of euclidean space that arise in computer vision
and signal processing.
 
== Extension to groups ==
 
The triple correlation may be defined for any locally compact group by using
the group's left-invariant [[Haar measure]]. It is easily shown that the resulting
object is invariant under left translation of the underlying function and
unbiased in additive Gaussian noise. What is more interesting is the question
of uniqueness : when two functions have the same triple correlation, how are the
functions related? For many cases of practical interest, the triple correlation
of a function on an abstract group uniquely identifies that function up to a single unknown group
action. This uniqueness is a mathematical result that relies on the [[Pontryagin duality]] theorem, the [[Tannaka-Krein duality]] theorem, and related results of Iwahori-Sugiura, and Tatsuuma. Algorithms exist for recovering bandlimited functions from their triple correlation on euclidean space, as well as rotation groups in two and three dimensions. There is also an interesting link with [[Wiener's tauberian theorem]]: any function whose translates are dense in <math>L_1(G)</math>, where G is a [[locally compact]] [[abelian group]], is also uniquely identified by its triple correlation.
 
== References ==
 
* K. Hasselman, W. Munk, and G. MacDonald (1963), "Bispectra of ocean waves", in ''Time Series Analysis'', M. Rosenblatt, Ed., New York: Wiley, 125-139.
 
* H. Gamo (1963), "Triple correlator of photoelectric fluctuations as a spectroscopic tool", ''Journal of Applied Physics'', Vol. 34, No. 4, (part 1), April 1963, pp 875–876.
 
* J. I. Yellott and G. J. Iverson (1992), "Uniqueness properties of higher-order autocorrelation functions,"  ''Journal of the Optical Society of America A'', 1992, 5, 388-404.
 
* R. Kakarala (1992) ''Triple correlation on groups'', Ph.D. Thesis, Department of Mathematics, University of California, Irvine.
 
* R. Kondor (2007), "A complete set of rotationally and translationally invariant features for images", http://arxiv.org/abs/cs.CV/0701127
 
[[Category:Integral transforms]]
[[Category:Fourier analysis]]
[[Category:Signal processing]]
[[Category:Covariance and correlation]]

Latest revision as of 04:16, 28 October 2014

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