文件列表:

TSPIHT\func_2_code.m (818, 2014-01-04)
TSPIHT\func_2_decode.m (1137, 2014-01-04)
TSPIHT\func_4_code.m (1251, 2014-01-04)
TSPIHT\func_4_decode.asv (1540, 2014-01-04)
TSPIHT\func_4_decode.m (1508, 2014-01-04)
TSPIHT\func_MyDescendant.m (710, 2014-01-04)
TSPIHT\func_ReadRaw.m (263, 2014-01-04)
TSPIHT\func_SPIHT_Dec.m (9539, 2014-01-04)
TSPIHT\func_SPIHT_Enc.m (9644, 2014-01-04)
TSPIHT\img_lena.bmp (263222, 2014-01-03)
TSPIHT\listorder.m (688, 2010-08-08)
TSPIHT\main_TSPIHT.m (1681, 2014-01-04)
TSPIHT\Thumbs.db (5632, 2010-04-02)
TSPIHT\wavecdf97.m (9578, 2010-02-04)
license.txt (1312, 2014-03-09)

just run main_TSPIHT.m If you find this tool useful, please cite it as 黄可坤. 基于二叉树的改进SPIHT算法[J]. 计算机工程, 2012, 38(15):218-221. Ke-Kun Huang. Improved SPIHT Algorithm Based on Binary Tree[J]. Computer Engineering, 2012, 38(15):218-221. For any question, please contact Ke-Kun Huang 基于二叉树的改进SPIHT算法 黄可坤 (嘉应学院数学学院，广东梅州, 514015) 摘 要：为在保持多级树集合分裂(SPIHT)算法编码速度的同时提高其性能，提出一种基于二叉树的改进SPIHT算法。对D型集合分裂得到的4 个系数进行二叉树编码，优先编码L 型集合的重要性，并以较高的概率提前判断二叉树根节点的重要性，从而提高编码效率。实验结果表明，该算法的执行速度与SPIHT 算法相当，且具有较高的峰值信噪比。 关键词：图像压缩；多级树集合分裂；零树编码；嵌入式编码；二叉树编码；小波变换 Improved SPIHT Algorithm Based on Binary Tree HUANG Ke-kun (Department of Mathematics， Jiaying University, Meizhou Guangdong 514015, ***) 【Abstract】In order to raise the performance of Set Partitioning in Hierarchical Trees(SPIHT) algorithm and maintain the encoding speed, an improved SPIHT algorithm based on binary tree is proposed. Four coefficients splited by D-type sets are coded by binary tree. Through coding the significance of L-type sets first, the algorithm can determine the significance of the root of the binary tree in advance with high probability, so as to further improve the coding efficiency. Experimental results show that the speed of the proposed algorithm is as fast as SPIHT algorithm, and it can improve Peak Signal to Noise Ratio(PSNR). 【Key words】image compression; Set Partitioning in Hierarchical Trees(SPIHT); zero tree coding; embedded coding; binary tree coding; wavelet transform

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