基于奇异值分解和Contourlet变换的图像压缩算法

摘要

随着互联网的飞速发展，产生大量的图像信息。为了减小存储并提高图像质量，提出了一种基于奇异值分解和Contourlet变化结合的有损图像压缩算法。该算法先对图像进行奇异值分解，根据奇异值对图像信号的贡献选取适当的奇异值来实现图像压缩，再对图像进行Contourlet变换和量化，实现图像二级压缩。将该算法和图像奇异值分解直接压缩算法、Contourlet变换压缩算法进行实验比较，结果表明，该算法比图像奇异值分解直接压缩算法、Contourlet变换压缩算法有更好的性能，在同样的压缩比情况下能获得更高的峰值信噪比和SSIM。%With the rapid development of Internet,image information is growing.In order to reduce the storage and improve the image quality,the paper proposed a new image compression algorithm that combined SVD and Contourlet transform.The image was decomposed by singular value decomposition.According to the contribution of singular value to the image signal,the algo-rithm selected the appropriate singular value to realize image compression.Then it compressed the image again using Contourlet transform compression algorithm.Compared with the singular value decomposition algorithm and Contourlet transform compres-sion algorithm,the results show that the proposed algorithm has better performance than singular value decomposition algorithm and Contourlet transform compression algorithm.The proposed algorithm can obtain higher peak signal to noise ratio and SSIM in the same compression ratio.