Because the CWT is a redundant transform, there is not a unique way to define the inverse. The inverse CWT implemented in the Wavelet Toolbox™ uses the analytic Morse wavelet and L1 normalization.
The inverse CWT is classically presented in the double-integral form. Assume you have a wavelet with a Fourier transform that satisfies the admissibility condition:
For wavelets satisfying the admissibility condition and finite-energy functions, f(t), you can define the inverse CWT as:
For analyzing wavelets and functions satisfying the following conditions, a single integral formula for the inverse CWT exists. These conditions are:
The analyzed function, f(t), is real-valued and the analyzing wavelet has a real-valued Fourier transform.
The analyzed function, f(t), is real-valued 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.
The preceding conditions constrain the set of possible analyzing
wavelets. Wavelets supported by
analytic. Because the toolbox only supports the analysis of real-valued
functions, the real-valued condition on the analyzed function is always
To motivate the single integral formula, let ψ1 and ψ2 be two wavelets that satisfy the following two-wavelet admissibility condition:
Define the constant:
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:
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
The preceding equation demonstrates 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.
icwt implements a discretized
version of the above integral.