提出了新的多光谱图像压缩方案,直方图变换的三维分层树的集划分(3D SPIHT)压缩编码算法。基于多光谱图像的成像特点,在去相关之前,提出一种可逆的直方图变换方法对多光谱各波段图像灰度值进行调整,来提高各波段间的相关性,然后再对变换后的图像利用K_L和二维小波变换去除谱间冗余和空间冗余。小波编码采用两种编码方案:3D_SPIHT以及对它进行改进后的三维位平面的SPIHT算法,并对两者进行了比较。实验表明,采用直方图变换的这两种方法都获得了良好的效果,比没变换前有更好的图像质量和压缩性能。 A new multi-spectral image compression scheme and 3D SPIHT compression coding algorithm for histogram transformation are proposed. Based on the imaging characteristics of multi-spectral images, a reversible histogram transformation method is proposed to adjust the gray values ​​of the multi-spectral images to improve the correlation between the bands before the decorrelation. Then, the transformed images Using K_L and two-dimensional wavelet transform to remove spectral redundancy and spatial redundancy. Wavelet coding uses two coding schemes: 3D_SPIHT and the improved SPIHT algorithm for the three-dimensional bit plane, and compares the two. Experiments show that both of the two methods using histogram transform have good effect and have better image quality and compression performance than those without transform.