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In mathematics, the Haar wavelet is a sequence of rescaled "square-shaped" functions which together form a
wavelet A wavelet is a wave-like oscillation with an amplitude that begins at zero, increases or decreases, and then returns to zero one or more times. Wavelets are termed a "brief oscillation". A taxonomy of wavelets has been established, based on the num ...
family or basis. Wavelet analysis is similar to Fourier analysis in that it allows a target function over an interval to be represented in terms of an orthonormal basis. The Haar sequence is now recognised as the first known wavelet basis and extensively used as a teaching example. The Haar sequence was proposed in 1909 by
Alfréd Haar Alfréd Haar ( hu, Haar Alfréd; 11 October 1885, Budapest – 16 March 1933, Szeged) was a Kingdom of Hungary, Hungarian mathematician. In 1904 he began to study at the University of Göttingen. His doctorate was supervised by David Hil ...
. Haar used these functions to give an example of an orthonormal system for the space of square-integrable functions on the
unit interval In mathematics, the unit interval is the closed interval , that is, the set of all real numbers that are greater than or equal to 0 and less than or equal to 1. It is often denoted ' (capital letter ). In addition to its role in real analysis ...
  , 1 The study of wavelets, and even the term "wavelet", did not come until much later. As a special case of the
Daubechies wavelet The Daubechies wavelets, based on the work of Ingrid Daubechies, are a family of orthogonal wavelets defining a discrete wavelet transform and characterized by a maximal number of vanishing moments for some given support. With each wavelet type ...
, the Haar wavelet is also known as Db1. The Haar wavelet is also the simplest possible wavelet. The technical disadvantage of the Haar wavelet is that it is not continuous, and therefore not
differentiable In mathematics, a differentiable function of one real variable is a function whose derivative exists at each point in its domain. In other words, the graph of a differentiable function has a non-vertical tangent line at each interior point in its ...
. This property can, however, be an advantage for the analysis of signals with sudden transitions ( discrete signals), such as monitoring of tool failure in machines. The Haar wavelet's mother wavelet function \psi(t) can be described as : \psi(t) = \begin 1 \quad & 0 \leq t < \frac,\\ -1 & \frac \leq t < 1,\\ 0 &\mbox \end Its scaling function \varphi(t) can be described as : \varphi(t) = \begin1 \quad & 0 \leq t < 1,\\0 &\mbox\end


Haar functions and Haar system

For every pair ''n'', ''k'' of integers in \mathbb, the Haar function ''ψ''''n'',''k'' is defined on the real line \mathbb by the formula : \psi_(t) = 2^ \psi(2^n t-k), \quad t \in \mathbb. This function is supported on the right-open interval , ''i.e.'', it vanishes outside that interval. It has integral 0 and norm 1 in the Hilbert space  ''L''2(\mathbb), : \int_ \psi_(t) \, d t = 0, \quad \, \psi_\, ^2_ = \int_ \psi_(t)^2 \, d t = 1. The Haar functions are pairwise orthogonal, : \int_ \psi_(t) \psi_(t) \, d t = \delta_ \delta_, where \delta_ represents the
Kronecker delta In mathematics, the Kronecker delta (named after Leopold Kronecker) is a function of two variables, usually just non-negative integers. The function is 1 if the variables are equal, and 0 otherwise: \delta_ = \begin 0 &\text i \neq j, \\ 1 & ...
. Here is the reason for orthogonality: when the two supporting intervals I_ and I_ are not equal, then they are either disjoint, or else the smaller of the two supports, say I_, is contained in the lower or in the upper half of the other interval, on which the function \psi_ remains constant. It follows in this case that the product of these two Haar functions is a multiple of the first Haar function, hence the product has integral 0. The Haar system on the real line is the set of functions :\ \cup \. It is complete in ''L''2(\mathbb): ''The Haar system on the line is an orthonormal basis in'' ''L''2(\mathbb).


Haar wavelet properties

The Haar wavelet has several notable properties: #Any continuous real function with compact support can be approximated uniformly by linear combinations of \varphi(t),\varphi(2t),\varphi(4t),\dots,\varphi(2^n t),\dots and their shifted functions. This extends to those function spaces where any function therein can be approximated by continuous functions. #Any continuous real function on , 1can be approximated uniformly on , 1by linear combinations of the constant function 1, \psi(t),\psi(2t),\psi(4t),\dots,\psi(2^n t),\dots and their shifted functions. # Orthogonality in the form      \int_^2^\psi(2^n t-k)\psi(2^ t - k_1)\, dt = \delta_\delta_. Here, \delta_ represents the
Kronecker delta In mathematics, the Kronecker delta (named after Leopold Kronecker) is a function of two variables, usually just non-negative integers. The function is 1 if the variables are equal, and 0 otherwise: \delta_ = \begin 0 &\text i \neq j, \\ 1 & ...
. The
dual function In mathematical optimization theory, duality or the duality principle is the principle that optimization problems may be viewed from either of two perspectives, the primal problem or the dual problem. If the primal is a minimization problem then th ...
of ψ(''t'') is ψ(''t'') itself. # Wavelet/scaling functions with different scale ''n'' have a functional relationship: since :: \begin \varphi(t) &= \varphi(2t)+\varphi(2t-1)\\ 2em \psi(t) &= \varphi(2t)-\varphi(2t-1), \end :it follows that coefficients of scale ''n'' can be calculated by coefficients of scale ''n+1'': :If \chi_w(k, n)= 2^\int_^\infty x(t)\varphi(2^nt-k)\, dt :and \Chi_w(k, n)= 2^\int_^\infty x(t)\psi(2^nt-k)\, dt :then :: \chi_w(k,n)= 2^ \bigl( \chi_w(2k,n+1)+\chi_w(2k+1,n+1) \bigr) :: \Chi_w(k,n)= 2^ \bigl( \chi_w(2k,n+1)-\chi_w(2k+1,n+1) \bigr).


Haar system on the unit interval and related systems

In this section, the discussion is restricted to the
unit interval In mathematics, the unit interval is the closed interval , that is, the set of all real numbers that are greater than or equal to 0 and less than or equal to 1. It is often denoted ' (capital letter ). In addition to its role in real analysis ...
, 1and to the Haar functions that are supported on , 1 The system of functions considered by Haar in 1910, called the Haar system on , 1'' in this article, consists of the subset of Haar wavelets defined as :\, with the addition of the constant function 1 on , 1 In Hilbert space terms, this Haar system on , 1is a complete orthonormal system, ''i.e.'', an orthonormal basis, for the space ''L''2( , 1 of square integrable functions on the unit interval. The Haar system on , 1—with the constant function 1 as first element, followed with the Haar functions ordered according to the
lexicographic Lexicography is the study of lexicons, and is divided into two separate academic disciplines. It is the art of compiling dictionaries. * Practical lexicography is the art or craft of compiling, writing and editing dictionaries. * Theoretica ...
ordering of couples — is further a monotone Schauder basis for the space ''L''''p''( , 1 when .see p. 3 in J. Lindenstrauss, L. Tzafriri, (1977), "Classical Banach Spaces I, Sequence Spaces", Ergebnisse der Mathematik und ihrer Grenzgebiete 92, Berlin: Springer-Verlag, . This basis is unconditional when . There is a related
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consisting of sums of Haar functions, :r_n(t) = 2^ \sum_^ \psi_(t), \quad t \in
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random variables with mean 0. The Khintchine inequality expresses the fact that in all the spaces ''L''''p''( , 1, , the Rademacher sequence is
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to the unit vector basis in ℓ''2''. In particular, the closed linear span of the Rademacher sequence in ''L''''p''( , 1, , is isomorphic to ℓ''2''.


The Faber–Schauder system

The Faber–Schauder systemFaber, Georg (1910), "Über die Orthogonalfunktionen des Herrn Haar", ''Deutsche Math.-Ver'' (in German) 19: 104–112. ; http://www-gdz.sub.uni-goettingen.de/cgi-bin/digbib.cgi?PPN37721857X ; http://resolver.sub.uni-goettingen.de/purl?GDZPPN002122553 is the family of continuous functions on , 1consisting of the constant function 1, and of multiples of indefinite integrals of the functions in the Haar system on  , 1 chosen to have norm 1 in the
maximum norm In mathematical analysis, the uniform norm (or ) assigns to real- or complex-valued bounded functions defined on a set the non-negative number :\, f\, _\infty = \, f\, _ = \sup\left\. This norm is also called the , the , the , or, when the ...
. This system begins with ''s''0 = 1, then is the indefinite integral vanishing at 0 of the function 1, first element of the Haar system on , 1 Next, for every integer , functions are defined by the formula : s_(t) = 2^ \int_0^t \psi_(u) \, d u, \quad t \in
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\ 0 \le k < 2^n. These functions are continuous, piecewise linear, supported by the interval that also supports . The function is equal to 1 at the midpoint of the interval , linear on both halves of that interval. It takes values between 0 and 1 everywhere. The Faber–Schauder system is a Schauder basis for the space ''C''( , 1 of continuous functions on , 1 For every ''f'' in ''C''( , 1, the partial sum : f_ = a_0 s_0 + a_1 s_1 + \sum_^ \Bigl( \sum_^ a_ s_ \Bigr) \in C(
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of the
series expansion In mathematics, a series expansion is an expansion of a function into a series, or infinite sum. It is a method for calculating a function that cannot be expressed by just elementary operators (addition, subtraction, multiplication and divisi ...
of ''f'' in the Faber–Schauder system is the continuous piecewise linear function that agrees with ''f'' at the points , where . Next, the formula : f_ - f_ = \sum_^ \bigl( f(x_) - f_(x_) \bigr) s_ = \sum_^ a_ s_ gives a way to compute the expansion of ''f'' step by step. Since ''f'' is
uniformly continuous In mathematics, a real function f of real numbers is said to be uniformly continuous if there is a positive real number \delta such that function values over any function domain interval of the size \delta are as close to each other as we want. In ...
, the sequence converges uniformly to ''f''. It follows that the Faber–Schauder series expansion of ''f'' converges in ''C''( , 1, and the sum of this series is equal to ''f''.


The Franklin system

The Franklin system is obtained from the Faber–Schauder system by the Gram–Schmidt orthonormalization procedure. Since the Franklin system has the same linear span as that of the Faber–Schauder system, this span is dense in ''C''( , 1, hence in ''L''2( , 1. The Franklin system is therefore an orthonormal basis for ''L''2( , 1, consisting of continuous piecewise linear functions. P. Franklin proved in 1928 that this system is a Schauder basis for ''C''( , 1. The Franklin system is also an unconditional Schauder basis for the space ''L''''p''( , 1 when .S. V. Bočkarev, ''Existence of a basis in the space of functions analytic in the disc, and some properties of Franklin's system''. Mat. Sb. 95 (1974), 3–18 (Russian). Translated in Math. USSR-Sb. 24 (1974), 1–16. The Franklin system provides a Schauder basis in the disk algebra ''A''(''D''). This was proved in 1974 by Bočkarev, after the existence of a basis for the disk algebra had remained open for more than forty years. Bočkarev's construction of a Schauder basis in ''A''(''D'') goes as follows: let ''f'' be a complex valued Lipschitz function on , π then ''f'' is the sum of a cosine series with absolutely summable coefficients. Let ''T''(''f'') be the element of ''A''(''D'') defined by the complex power series with the same coefficients, : \left\ \longrightarrow \left\. Bočkarev's basis for ''A''(''D'') is formed by the images under ''T'' of the functions in the Franklin system on  , π Bočkarev's equivalent description for the mapping ''T'' starts by extending ''f'' to an even Lipschitz function ''g''1 on minus;π, π identified with a Lipschitz function on the
unit circle In mathematics, a unit circle is a circle of unit radius—that is, a radius of 1. Frequently, especially in trigonometry, the unit circle is the circle of radius 1 centered at the origin (0, 0) in the Cartesian coordinate system in the Eucli ...
 T. Next, let ''g''2 be the conjugate function of ''g''1, and define ''T''(''f'') to be the function in ''A''(''D'') whose value on the boundary T of ''D'' is equal to . When dealing with 1-periodic continuous functions, or rather with continuous functions ''f'' on , 1such that , one removes the function from the Faber–Schauder system, in order to obtain the periodic Faber–Schauder system. The periodic Franklin system is obtained by orthonormalization from the periodic Faber–-Schauder system.See p. 161, III.D.20 and p. 192, III.E.17 in One can prove Bočkarev's result on ''A''(''D'') by proving that the periodic Franklin system on , 2πis a basis for a Banach space ''A''''r'' isomorphic to ''A''(''D''). The space ''A''''r'' consists of complex continuous functions on the unit circle T whose conjugate function is also continuous.


Haar matrix

The 2×2 Haar matrix that is associated with the Haar wavelet is : H_2 = \begin 1 & 1 \\ 1 & -1 \end. Using the discrete wavelet transform, one can transform any sequence (a_0,a_1,\dots,a_,a_) of even length into a sequence of two-component-vectors \left(\left(a_0,a_1\right),\left(a_2,a_3\right),\dots,\left(a_,a_\right)\right) . If one right-multiplies each vector with the matrix H_2 , one gets the result \left(\left(s_0,d_0\right),\dots,\left(s_n,d_n\right)\right) of one stage of the fast Haar-wavelet transform. Usually one separates the sequences ''s'' and ''d'' and continues with transforming the sequence ''s''. Sequence ''s'' is often referred to as the ''averages'' part, whereas ''d'' is known as the ''details'' part. If one has a sequence of length a multiple of four, one can build blocks of 4 elements and transform them in a similar manner with the 4×4 Haar matrix : H_4 = \begin 1 & 1 & 1 & 1 \\ 1 & 1 & -1 & -1 \\ 1 & -1 & 0 & 0\\ 0 & 0 & 1 & -1 \end, which combines two stages of the fast Haar-wavelet transform. Compare with a Walsh matrix, which is a non-localized 1/–1 matrix. Generally, the 2N×2N Haar matrix can be derived by the following equation. : H_ = \begin H_ \otimes
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\\ I_ \otimes , -1\end :where I_ = \begin 1 & 0 & \dots & 0 \\ 0 & 1 & \dots & 0 \\ \vdots & \vdots & \ddots & \vdots \\ 0 & 0 & \dots & 1 \end and \otimes is the Kronecker product. The Kronecker product of A \otimes B, where A is an m×n matrix and B is a p×q matrix, is expressed as : A \otimes B = \begin a_B & \dots & a_B \\ \vdots & \ddots & \vdots \\ a_B & \dots & a_B\end. An un-normalized 8-point Haar matrix H_8 is shown below : H_ = \begin 1&1&1&1&1&1&1&1 \\ 1&1&1&1&-1&-1&-1&-1 \\ 1&1&-1&-1&0&0&0&0& \\ 0&0&0&0&1&1&-1&-1 \\ 1&-1&0&0&0&0&0&0& \\ 0&0&1&-1&0&0&0&0 \\ 0&0&0&0&1&-1&0&0& \\ 0&0&0&0&0&0&1&-1 \end. Note that, the above matrix is an un-normalized Haar matrix. The Haar matrix required by the Haar transform should be normalized. From the definition of the Haar matrix H, one can observe that, unlike the Fourier transform, H has only real elements (i.e., 1, -1 or 0) and is non-symmetric. Take the 8-point Haar matrix H_8 as an example. The first row of H_8 measures the average value, and the second row of H_8 measures a low frequency component of the input vector. The next two rows are sensitive to the first and second half of the input vector respectively, which corresponds to moderate frequency components. The remaining four rows are sensitive to the four section of the input vector, which corresponds to high frequency components.


Haar transform

The Haar transform is the simplest of the
wavelet transform In mathematics, a wavelet series is a representation of a square-integrable ( real- or complex-valued) function by a certain orthonormal series generated by a wavelet. This article provides a formal, mathematical definition of an orthonormal ...
s. This transform cross-multiplies a function against the Haar wavelet with various shifts and stretches, like the Fourier transform cross-multiplies a function against a sine wave with two phases and many stretches.The Haar Transform
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Introduction

The Haar transform is one of the oldest transform functions, proposed in 1910 by the Hungarian mathematician
Alfréd Haar Alfréd Haar ( hu, Haar Alfréd; 11 October 1885, Budapest – 16 March 1933, Szeged) was a Kingdom of Hungary, Hungarian mathematician. In 1904 he began to study at the University of Göttingen. His doctorate was supervised by David Hil ...
. It is found effective in applications such as signal and image compression in electrical and computer engineering as it provides a simple and computationally efficient approach for analysing the local aspects of a signal. The Haar transform is derived from the Haar matrix. An example of a 4x4 Haar transformation matrix is shown below. :H_4 = \frac \begin 1 & 1 & 1 & 1 \\ 1 & 1 & -1 & -1 \\ \sqrt & -\sqrt & 0 & 0 \\ 0 & 0 & \sqrt & -\sqrt\end The Haar transform can be thought of as a sampling process in which rows of the transformation matrix act as samples of finer and finer resolution. Compare with the
Walsh transform The Hadamard transform (also known as the Walsh–Hadamard transform, Hadamard–Rademacher–Walsh transform, Walsh transform, or Walsh–Fourier transform) is an example of a generalized class of Fourier transforms. It performs an orthogonal ...
, which is also 1/–1, but is non-localized.


Property

The Haar transform has the following properties : 1. No need for multiplications. It requires only additions and there are many elements with zero value in the Haar matrix, so the computation time is short. It is faster than
Walsh transform The Hadamard transform (also known as the Walsh–Hadamard transform, Hadamard–Rademacher–Walsh transform, Walsh transform, or Walsh–Fourier transform) is an example of a generalized class of Fourier transforms. It performs an orthogonal ...
, whose matrix is composed of +1 and −1. : 2. Input and output length are the same. However, the length should be a power of 2, i.e. N = 2^k, k\in \mathbb. : 3. It can be used to analyse the localized feature of signals. Due to the orthogonal property of the Haar function, the frequency components of input signal can be analyzed.


Haar transform and Inverse Haar transform

The Haar transform ''y''''n'' of an n-input function ''x''''n'' is : y_n = H_n x_n The Haar transform matrix is real and orthogonal. Thus, the inverse Haar transform can be derived by the following equations. : H = H^*, H^ = H^T, \text HH^T = I : where I is the identity matrix. For example, when n = 4 : H_4^H_4 = \frac\begin 1&1&\sqrt&0 \\ 1&1&-\sqrt&0 \\ 1&-1&0&\sqrt \\ 1&-1&0&-\sqrt\end \cdot\; \frac\begin 1&1&1&1 \\ 1&1&-1&-1 \\ \sqrt&-\sqrt&0&0 \\ 0&0&\sqrt&-\sqrt\end = \begin 1&0&0&0 \\ 0&1&0&0 \\ 0&0&1&0 \\ 0&0&0&1 \end Thus, the inverse Haar transform is : x_ = H^y_


Example

The Haar transform coefficients of a n=4-point signal x_ = ,2,3,4 can be found as : y_ = H_4 x_4 = \frac\begin 1&1&1&1 \\ 1&1&-1&-1 \\ \sqrt&-\sqrt&0&0 \\ 0&0&\sqrt&-\sqrt\end \begin 1 \\ 2 \\ 3 \\ 4\end = \begin 5 \\ -2 \\ -1/\sqrt \\ -1/\sqrt\end The input signal can then be perfectly reconstructed by the inverse Haar transform : \hat = H_^y_ = \frac\begin 1&1&\sqrt&0 \\ 1&1&-\sqrt&0 \\ 1&-1&0&\sqrt \\ 1&-1&0&-\sqrt\end \begin 5 \\ -2 \\ -1/\sqrt \\ -1/\sqrt\end = \begin 1 \\ 2 \\ 3 \\ 4 \end


See also

*
Dimension reduction Dimensionality reduction, or dimension reduction, is the transformation of data from a high-dimensional space into a low-dimensional space so that the low-dimensional representation retains some meaningful properties of the original data, ideally ...
* Walsh matrix *
Walsh transform The Hadamard transform (also known as the Walsh–Hadamard transform, Hadamard–Rademacher–Walsh transform, Walsh transform, or Walsh–Fourier transform) is an example of a generalized class of Fourier transforms. It performs an orthogonal ...
*
Wavelet A wavelet is a wave-like oscillation with an amplitude that begins at zero, increases or decreases, and then returns to zero one or more times. Wavelets are termed a "brief oscillation". A taxonomy of wavelets has been established, based on the num ...
* Chirplet *
Signal In signal processing, a signal is a function that conveys information about a phenomenon. Any quantity that can vary over space or time can be used as a signal to share messages between observers. The '' IEEE Transactions on Signal Processing' ...
* Haar-like feature * Strömberg wavelet *
Dyadic transformation The dyadic transformation (also known as the dyadic map, bit shift map, 2''x'' mod 1 map, Bernoulli map, doubling map or sawtooth map) is the mapping (i.e., recurrence relation) : T: , 1) \to [0, 1)^\infty : x \mapsto (x_0, x_1, x_2, ...


Notes


References

* * Charles K. Chui, ''An Introduction to Wavelets'', (1992), Academic Press, San Diego, * English Translation of Haar's seminal article


External links

*
Free Haar wavelet filtering implementation and interactive demo

Free Haar wavelet denoising and lossy signal compression


Haar transform











{{DEFAULTSORT:Haar Wavelet Orthogonal wavelets