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Wikipedia

Orthogonal wavelet

An orthogonal wavelet is a wavelet whose associated wavelet transform is orthogonal. That is, the inverse wavelet transform is the adjoint of the wavelet transform. If this condition is weakened one may end up with biorthogonal wavelets.

Basics

The scaling function is a refinable function. That is, it is a fractal functional equation, called the refinement equation (twin-scale relation or dilation equation):

 ,

where the sequence   of real numbers is called a scaling sequence or scaling mask. The wavelet proper is obtained by a similar linear combination,

 ,

where the sequence   of real numbers is called a wavelet sequence or wavelet mask.

A necessary condition for the orthogonality of the wavelets is that the scaling sequence is orthogonal to any shifts of it by an even number of coefficients:

 ,

where   is the Kronecker delta.

In this case there is the same number M=N of coefficients in the scaling as in the wavelet sequence, the wavelet sequence can be determined as  . In some cases the opposite sign is chosen.

Vanishing moments, polynomial approximation and smoothness

A necessary condition for the existence of a solution to the refinement equation is that there exists a positive integer A such that (see Z-transform):

 

The maximally possible power A is called polynomial approximation order (or pol. app. power) or number of vanishing moments. It describes the ability to represent polynomials up to degree A-1 with linear combinations of integer translates of the scaling function.

In the biorthogonal case, an approximation order A of   corresponds to A vanishing moments of the dual wavelet  , that is, the scalar products of   with any polynomial up to degree A-1 are zero. In the opposite direction, the approximation order à of   is equivalent to à vanishing moments of  . In the orthogonal case, A and à coincide.

A sufficient condition for the existence of a scaling function is the following: if one decomposes  , and the estimate

 

holds for some  , then the refinement equation has a n times continuously differentiable solution with compact support.

Examples

  • Suppose   then  , and the estimate holds for n=A-2. The solutions are Schoenbergs B-splines of order A-1, where the (A-1)-th derivative is piecewise constant, thus the (A-2)-th derivative is Lipschitz-continuous. A=1 corresponds to the index function of the unit interval.
  • A=2 and p linear may be written as
 
Expansion of this degree 3 polynomial and insertion of the 4 coefficients into the orthogonality condition results in   The positive root gives the scaling sequence of the D4-wavelet, see below.

References

  • Ingrid Daubechies: Ten Lectures on Wavelets, SIAM 1992.
  • Proc. 1st NJIT Symposium on Wavelets, Subbands and Transforms, April 1990.

orthogonal, wavelet, orthogonal, wavelet, wavelet, whose, associated, wavelet, transform, orthogonal, that, inverse, wavelet, transform, adjoint, wavelet, transform, this, condition, weakened, with, biorthogonal, wavelets, contents, basics, vanishing, moments,. An orthogonal wavelet is a wavelet whose associated wavelet transform is orthogonal That is the inverse wavelet transform is the adjoint of the wavelet transform If this condition is weakened one may end up with biorthogonal wavelets Contents 1 Basics 2 Vanishing moments polynomial approximation and smoothness 2 1 Examples 3 ReferencesBasics EditThe scaling function is a refinable function That is it is a fractal functional equation called the refinement equation twin scale relation or dilation equation ϕ x k 0 N 1 a k ϕ 2 x k displaystyle phi x sum k 0 N 1 a k phi 2x k where the sequence a 0 a N 1 displaystyle a 0 dots a N 1 of real numbers is called a scaling sequence or scaling mask The wavelet proper is obtained by a similar linear combination ps x k 0 M 1 b k ϕ 2 x k displaystyle psi x sum k 0 M 1 b k phi 2x k where the sequence b 0 b M 1 displaystyle b 0 dots b M 1 of real numbers is called a wavelet sequence or wavelet mask A necessary condition for the orthogonality of the wavelets is that the scaling sequence is orthogonal to any shifts of it by an even number of coefficients n Z a n a n 2 m 2 d m 0 displaystyle sum n in mathbb Z a n a n 2m 2 delta m 0 where d m n displaystyle delta m n is the Kronecker delta In this case there is the same number M N of coefficients in the scaling as in the wavelet sequence the wavelet sequence can be determined as b n 1 n a N 1 n displaystyle b n 1 n a N 1 n In some cases the opposite sign is chosen Vanishing moments polynomial approximation and smoothness EditA necessary condition for the existence of a solution to the refinement equation is that there exists a positive integer A such that see Z transform 1 Z A a Z a 0 a 1 Z a N 1 Z N 1 displaystyle 1 Z A a Z a 0 a 1 Z dots a N 1 Z N 1 The maximally possible power A is called polynomial approximation order or pol app power or number of vanishing moments It describes the ability to represent polynomials up to degree A 1 with linear combinations of integer translates of the scaling function In the biorthogonal case an approximation order A of ϕ displaystyle phi corresponds to A vanishing moments of the dual wavelet ps displaystyle tilde psi that is the scalar products of ps displaystyle tilde psi with any polynomial up to degree A 1 are zero In the opposite direction the approximation order A of ϕ displaystyle tilde phi is equivalent to A vanishing moments of ps displaystyle psi In the orthogonal case A and A coincide A sufficient condition for the existence of a scaling function is the following if one decomposes a Z 2 1 A 1 Z A p Z displaystyle a Z 2 1 A 1 Z A p Z and the estimate 1 sup t 0 2 p p e i t lt 2 A 1 n displaystyle 1 leq sup t in 0 2 pi left p e it right lt 2 A 1 n holds for some n N displaystyle n in mathbb N then the refinement equation has a n times continuously differentiable solution with compact support Examples Edit Suppose p Z 1 displaystyle p Z 1 then a Z 2 1 A 1 Z A displaystyle a Z 2 1 A 1 Z A and the estimate holds for n A 2 The solutions are Schoenbergs B splines of order A 1 where the A 1 th derivative is piecewise constant thus the A 2 th derivative is Lipschitz continuous A 1 corresponds to the index function of the unit interval A 2 and p linear may be written asa Z 1 4 1 Z 2 1 Z c 1 Z displaystyle a Z frac 1 4 1 Z 2 1 Z c 1 Z dd Expansion of this degree 3 polynomial and insertion of the 4 coefficients into the orthogonality condition results in c 2 3 displaystyle c 2 3 The positive root gives the scaling sequence of the D4 wavelet see below References EditIngrid Daubechies Ten Lectures on Wavelets SIAM 1992 Proc 1st NJIT Symposium on Wavelets Subbands and Transforms April 1990 Retrieved from https en wikipedia org w index php title Orthogonal wavelet amp oldid 1117256324, wikipedia, wiki, book, books, library,

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