The change-point detection problem is one of the central problems in statistical inference and nonstationary signal processing. In this research, we incorporate the wavelet transform technique into the change-point detection framework and address several arising issues. We first apply the change detection algorithm in the wavelet domain, and discuss the advantages and disadvantages of the approach. Then, we consider the effect of down-sampling and the use of non-wavelet filters. Finally, we propose a new scheme for change detection based on the local energy feature, which shows some clear advantage of the wavelet transform approach.