Computes the multi-level discrete wavelet transform (DWT) of signal. This VI returns the approximation coefficients at the largest level and the detail coefficients at all levels for a 1D signal input. This VI returns the approximation coefficients and the detail coefficients at all levels for a 2D signal input. This VI computes the DWT at each level by using the lowpass analysis filters, the highpass analysis filters, and a decimation factor of 2. Wire data to the signal input to determine the polymorphic instance to use or manually select the instance.


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WA Discrete Wavelet Transform Details

The following illustration shows an example of a three-level discrete wavelet decomposition, where you set the levels input of this VI to 3. The length of the input signal is 16 points.

G1(z) denotes that the signal passes through a highpass filter. G0(z) denotes that the signal passes through a lowpass filter. G1(z) and G0(z) form the analysis filter bank. denotes a decimation on the signal with a factor of 2.

Using information in the previous illustration, you can see that the DWT coef output contains the approximation coefficients of the largest level and the details coefficients of each level. You also can see that the length output of this VI contains the following elements, where the last element is the length of the input signal:

Examples

Refer to the following VIs for examples of using the WA Discrete Wavelet Transform VI:

  • Image Compression VI: labview\examples\Wavelet Analysis\WAApplications
  • Get and Set Single Level Detail Coefficients VI: labview\examples\Wavelet Analysis\WAGettingStarted
  • Wavelet Transform and Reconstruction with Image VI: labview\examples\Wavelet Analysis\WAGettingStarted
  • Piece Polynomial Function Approx and Comp VI: labview\examples\Wavelet Analysis\WAGettingStarted
  • Multiscale Analysis VI: labview\examples\Wavelet Analysis\WAApplications
  • Get and Set Approximation Coefficients VI: labview\examples\Wavelet Analysis\WAGettingStarted
  • ECG Compression VI: labview\examples\Wavelet Analysis\WAApplications