Math 2.0

Harmonic analysis on Euclidean spaces Wavelets Example

Coiflet

Builds on Multiresolution analysisScaling function and refinement equationVanishing moments of a wavelet

Example

Coiflets are a family of compactly supported orthonormal wavelets constructed by Ingrid Daubechies and named after Ronald Coifman. For an even integer L≥2L \ge 2, the coiflet of order LL is a real orthonormal wavelet ψ\psi with scaling function φ\varphi such that:

  1. ψ\psi has LL vanishing moments: ∫ℝxlψ(x) dx=0\int_{\R} x^l \psi(x) \, dx = 0 for l=0,1,…,L−1l = 0, 1, \dots, L-1.
  2. ∫ℝφ(x) dx=1\int_{\R} \varphi(x) \, dx = 1 and ∫ℝxlφ(x) dx=0\int_{\R} x^l \varphi(x) \, dx = 0 for l=1,…,L−1l = 1, \dots, L-1.

The low-pass filter of the coiflet of order LL has 3L3L coefficients, so φ\varphi and ψ\psi are supported on intervals of length 3L−13L - 1. For L=2L = 2 the filter has 66 coefficients.

Remarks

The vanishing moments of the scaling function are the distinctive feature. For a smooth function ff, they make the scaling coefficient ⟨f,φj,k⟩\ip{f}{\varphi_{j,k}} close to 2−j/2f(2−jk)2^{-j/2} f(2^{-j} k), where φj,k(x)=2j/2φ(2jx−k)\varphi_{j,k}(x) = 2^{j/2}\varphi(2^j x - k), with an error that is small to high order in 2−j2^{-j}. So samples of ff can be used directly as starting coefficients of the discrete wavelet transform. To get these extra conditions, coiflets need longer filters than the Daubechies wavelets with the same number of vanishing moments of ψ\psi. Coiflets are also closer to symmetric than Daubechies wavelets.

Reading path

To understand this page from the ground up, read these 4 pages in order. The foundations come first.

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  1. Multiresolution analysis concept
  2. Scaling function and refinement equation concept
  3. Vanishing moments of a wavelet concept
  4. Coiflet example

Further reading

  1. Web https://en.wikipedia.org/wiki/Coiflet
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MSC42C40, 65T60
Instance ofWavelet
UsesMultiresolution analysis, Scaling function and refinement equation, Vanishing moments of a wavelet
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