Multi-mother adaptive wavelet transform and its application in feature extraction

Adaptive wavelet transform, using an adaptive wavelet as a linear combination of different wavelets, has been applied in optical information processing successfully. Most of the adaptive wavelets are built by daughter wavelets from only one mother wavelet. In this paper, we construct a new adaptive wavelet for feature extraction under noise as prepossessing in face pattern recognition. To have the ability of de-noising, daughters for construction are generated by two different mother wavelets. We call this transform multi-mother adaptive wavelet transform. It is important that the new wavelet combines advantages of different mother wavelets. With artificial neural network, the parameters are adaptively computed. Simulation results show the wavelet is not only robust to noise, but also keep good recognition performance. In frequency domain, the spectrum of our wavelet is real and easy to be realized as an optical filter.