It is well known that most wavelet transform algorithms compute sampled coefficients of the continuous wavelet transform using the filter bank structure of the discrete wavelet transform (DWT). Although this method is efficient, noticeable computational savings have been obtained through an FFT-based implementation. The authors present a fast Hartley transform (FHT)-based implementation of the filter bank and show that noticeable overall computational savings can be obtained.