基于改进SPIHT的静态图像编码

Improved SPIHT Static Image Coding

本文在零树编码算法分析的基础上,针对SPIHT算法的不足,提出了一种新的零树编码算法。该算法以SPIHT为基础,改进了其零树结构及编码流程,同时引入LZC算法的标志位图思想,在保证恢复图像质量的前提下,降低了内存消耗,提高了编解码速度。仿真实验结果表明,相对于SPIHT算法而言,重构图像的峰值信噪比和直观图像质量,本文算法都表现出了优良的性能,尤其是在低比特率下表现跟明显。

In this paper, a new zero-tree improved SPIHT（set paetitioning in hierarchical trees） image compression coding algorithm based on analysis of the shortage of zero-tree SPHIT. The algorithm is based on SPIHT, and improves the structure of zero-tree and the procedure of coding. In the meanwhile, it broaches the mind of LZC algorithm＇ s symbol flag.Experimental results show that the algorithm has characteristics of higher coding and decoding rates, peak signal-to-noise ratio and compression ratio especially in low-bit, so the reconstructed image is lossless in the visual perception.