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Inverse Continuous Wavelet Transform

The icwt function implements the inverse CWT. Using icwt requires that you obtain the CWT from cwt.

Because the CWT is a redundant transform, there is not a unique way to define the inverse. The inverse CWT implemented in Wavelet Toolbox™ uses analytic wavelets and L1 normalization.

The inverse CWT is classically presented in the double-integral form. Assume you have a wavelet ψ with a Fourier transform that satisfies the admissibility condition:

Cψ=|ψ(ω)|2|ω|dω<

For wavelets satisfying the admissibility condition and finite-energy functions, f(t), you can define the inverse CWT as:

f(t)=1Cψab<f(t),ψa,b(t)>ψa,b(t)dbdaa

where ψa,b(t)=1aψ(tba).

For analyzing wavelets and functions satisfying the following condition, a single integral formula for the inverse CWT exists.

  • The analyzed function, f(t), has finite energy, and the Fourier transform of the analyzing wavelet has support only on the set of nonnegative frequencies. This is referred to as an analytic wavelet. A function whose Fourier transform only has support on the set of nonnegative frequencies must be complex-valued.

Wavelets supported by cwt are analytic.

To motivate the single integral formula, let ψ1 and ψ2 be two wavelets that satisfy the following two-wavelet admissibility condition:

|ψ1*(ω)||ψ2(ω)||ω|dω<

Define the constant:

Cψ1,ψ2=ψ1*(ω)ψ2(ω)|ω|dω

The above constant may be complex-valued. Let f(t) and g(t) be two finite energy functions. If the two-wavelet admissibility condition is satisfied, the following equality holds:

Cψ1,ψ2<f,g>=<f,ψ1><g,ψ2>*dbdaa

where < , > denotes the inner product, * denotes the complex conjugate, and the dependence of ψ1 and ψ2 on scale and position has been suppressed for convenience.

The key to the single integral formula for the inverse CWT is to recognize that the two-wavelet admissibility condition can be satisfied even if one of the wavelets is not admissible. In other words, it is not necessary that both ψ1 and ψ2 be separately admissible. You can also relax the requirements further by allowing one of the functions and wavelets to be distributions. By first letting g(t) be the Dirac delta function (a distribution) and also allowing ψ2 to be the Dirac delta function, you can derive the single integral formula for the inverse CWT.

  • When f(t) is real valued,

    f(t)=2Re{1Cψ1,δ0<f(t),ψ1(t)>daa}

    where Re{ } denotes the real part.

  • When f(t) is complex valued,

    f(t)=2Cψ1,δ<f(t),ψ1(t)>daa.

The preceding equations demonstrate that you can reconstruct the signal by summing the scaled CWT coefficients over all scales.

By summing the scaled CWT coefficients from select scales, you obtain an approximation to the original signal. This is useful in situations where your phenomenon of interest is localized in scale.

The icwt function implements a discretized version of the above integrals. You can also use analysis filters extracted from a cwtfilterbank object to invert the CWT. In this case, icwt uses the approximate synthesis filters, or dual frame, in the inversion.