CODEWITHSUNDEEP
conv-neural-networkwavelet
user50167
user50167

Reputation: 1

How will wavelet transforms be useful with CNN for image classification?

I am planning to use the wavelet transform to extract textural features from images for classification purpose. However, I am not sure about whether using wavelet transform is good choice and which type of wavelet should I choose?

Upvotes: 0

Views: 370

Answers (1)

alle_meije
alle_meije

Reputation: 2480

This is one example: the scattering transform. The difference from a regular CNN is that the filters don't emerge from training the network, but are based on a 3D basis with desirable properties. The case above is not a 'deep' network either: the wavelet 'footprints' are fed to an SVM.

The convolution filters learned in the first layers of image classification networks usually look like edge detectors, like wavelet filters. One way to use wavelets in CNN is to have them in the first layers and freeze them: don't change these layers during training.

Upvotes: 0

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