I am planning to use the discrete wavelet transform to extract textural features from grayscale images for classification purpose. However, I am not sure which type of wavelet should I choose? most of the studies I read, using Haar or Daubechies wavelets when extracting features from images. So, is there a way to determine which wavelet is suitable?
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You may test your images and observe wavelet coefficients in any resolution (level of decomposition, time/scale) that a wavelet transformation will return to you, based on which you may design a simple equation as an objective function to select the base function (e.g., Haar
, Daubechies 4
, Daubechies 12
, Morlet
, Coiflet
) for you by a simple for
loop.

Emma
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