Hermitian wavelet

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Hermitian wavelets are a family of discrete and continuous wavelets used in the constant and discrete Hermite wavelet transforms. The nth Hermitian wavelet is defined as the normalized nth derivative of a Gaussian distribution for each positive n:[1]Ψn(x)=(2n)n2cnHen(x)e12x2,where Hen(x) denotes the nth probabilist's Hermite polynomial. Each normalization coefficient cn is given by cn=(n12nΓ(n+12))12=(n12nπ2n(2n1)!!)12n. The function ΨLρ,μ(,) is said to be an admissible Hermite wavelet if it satisfies the admissibility condition:[2]

CΨ=n=0Ψ^(n)2n<

where Ψ^(n) are the terms of the Hermite transform of Ψ.

In computer vision and image processing, Gaussian derivative operators of different orders are frequently used as a basis for expressing various types of visual operations; see scale space and N-jet.[3]

Examples

The first three derivatives of the Gaussian function with μ=0,σ=1:f(t)=π1/4e(t2/2),are:f(t)=π1/4te(t2/2),f(t)=π1/4(t21)e(t2/2),f(3)(t)=π1/4(3tt3)e(t2/2),and their L2 norms f=2/2,f=3/2,f(3)=30/4.

Normalizing the derivatives yields three Hermitian wavelets:Ψ1(t)=2π1/4te(t2/2),Ψ2(t)=233π1/4(1t2)e(t2/2),Ψ3(t)=21530π1/4(t33t)e(t2/2).

See also

References

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