基于主成分分析和分层树集合划分的rHuffman算法图像压缩研究

摘要

In order to reduce the storage and improve the image quality of the compressed,a lossy image compression algorithm based on principal component analysis and set partitioning in hierarchical tree (SPIHT)compression algorithm is proposed.Firstly,the image is decomposed by principal component decomposition,and the main features are selected to realize image compression,then SPIHT algorithm is used to compress the image into wavelet coefficients of different subband.Finally,Huffman coding is employed to achieve two-level image compression. Comparing this algorithm with SPIHT algorithm,Huffman coding algorithm of SPIHT,JEPG 2000 and PCA compression algorithm, our experimental results demonstrate a better performance than other compression algorithms and can obtain higher PNSR and SSIM under the same compression ratio.%互联网的飞速发展,产生了大量的图像信息.为了减少图片占用的存储空间,提高图像质量,提出了一种将主成分分析(PCA)和分层树集合划分(SPIHT)压缩算法相结合的有损图像压缩算法.首先对图像进行主成分分解,选取主要特征值进行压缩,再利用SPIHT算法将图像分解成不同子带的小波系数进行压缩,对SPIHT压缩系数进行哈夫曼编码,实现图像二级压缩.将本文提出的算法与SPIHT、SPIHT的哈夫曼编码、JEPG2000、PCA压缩算法进行了比较,结果表明本算法较其他压缩算法具有更好的性能,在压缩比相同的情况下能获得更高的PNSR和SSIM.