Abstract:For the traditional dyadic wavelet transform, a lot of boundary treatments are needed when the data length is not 2 of integer power. Aiming at such a limitation, a new adaptive optimization wavelet transform algorithm was proposed. The core idea is analyzing the pending data to obtain the optimal approximate length, hence optimize the boundary treatment, while analyzing the optimal approximate length to select the wavelet transform bases adaptively. Compared with the traditional dyadic wavelet transform, the proposed algorithm hashigher speed, less boundary treatment, and greater data compression, etc. An image compression example was given to demonstrate the feasibility of the proposed algorithm.