Fast wavelet packet basis selection for block-partitioning image coding

Wavelet packet provides an effective representative tool for adaptive waveform analysis of a given signal. To construct an appropriate basis, the basis-selection criterion must be carefully designed. A rate-distortion based basis selection method was proposed in recent years, which can produce an optimal basis in the rate-distortion sense. However, this approach is extremely computationally intensive. Other criterions, such as the entropy based method, do not always produce an effective basis. In this work, we propose a distortion based basis-selection criterion with moderate computational complexity. Two basis selection procedures, i.e. greedy tree growing algorithm and optimal tree pruning algorithm are both evaluated. The experimental results show that, when adopting the same quantization and entropy coding methods, the coding performance of the proposed scheme is inferior to that of the rate-distortion optimized basis by only 0.11dB on the average, while the basis search procedure is sped up by a factor of 10.1 averagely