基于子带极值阶梯性的SPIHT算法改进方案

Modified SPIHT Algorithm Based on Ladder Property of Subband Extreme Value

多级树集合分裂算法(SPIHT)充分利用了小波分解后相同方向不同尺度子带图像间的相似性,取得了很好的压缩效果,在基于小波的图像编码方案中得到了广泛应用。该文利用子带极值的阶梯性对SPIHT算法进行了改进。理论分析和实验都证明了改进算法在复杂度有所降低的前提下有效地提高了压缩性能。

Set Partitioning in Hierarchical Trees （SPIHT） algorithm exploits the spatial self-similarity between subband in same spatial orientation, but not in same level. It achieves efficient result and applies in image coding based on wavelet. This paper exploits the ladder property between subband extreme value and modify SPIHT algorithm. Both theoretic analysis and experiment results confirm good compression performance and low complexity at the same time.