结合矢量量化的SPIHT算法用于多光谱图像压缩

Application of SPIHT with vector quantization to compression of multispectral

针对多波段遥感图像纹理复杂丰富、局部相关性较弱的特点,提出了结合矢量量化的SPIHT压缩算法。将经过小波变换后的遥感图像谱间相同位置的系数聚集构成矢量,根据高频子图的局部块纹理强弱进行自适应性的量化。使基于标量的SPIHT算法能够方便的处理矢量,有效去除数据间各类相关。实验表明,该方法对多波段遥感图像的压缩可以收到良好的效果,且算法具有良好的实时性,对单幅图像的压缩比和峰值信噪比(PSNR)均优于普通的二维SPIHT算法。

This article makes use of the characteristics of multispectral remote sensing images: the complex image veins and interboard dependencies, and proposes SPIHT compression algorithm joining the vector quantization. It puts the coefficients in the same position in the remote sensing spectral after wavelet transform, and then quantizes according the local vein of the high band image, so that the SPIHT algorithm based on the scalar can deal with the vector conveniently, and wipe off the dependencies among the data. The experiment shows that the proposed method has a good performance for the compression of the multispectral remote sensing images, the time complexity is low, and the compression ratio and PSNR for the signal image are both better than the original SPIHT algorithm.