基于小波变换和分段DPCM混合编码的多光谱遥感图像压缩算法

多光谱遥感图像的压缩要利用图像谱内及谱间的相关特性。该文在分析多光谱图像谱内和谱间相关特性的基础上,提出了对多光谱遥感图像进行压缩的分段 DPCM和 SPIHT相结合的混合压缩算法,即首先利用分段 DPCM算法去除谱间冗余,再利用高效的 SPIHT小波压缩算法对预测误差图像进行编码。实验取得了令人满意的效果,证明了该算法的有效性。

Multispectral imagery compression by hybrid DWT and partitioning DPCM

Compression of multispectral imagery is based on reducing redundancies in both the spatial domain and the spectral domain. In this paper, a new hybrid compression algorithm using partitioning DPCM and SPIHT is proposed on the base of analyzing the spatial and spectral correlation features of multispectral imagery. A first-order predictor is designed for de-correlating the spectral redundancy and creating error images for later use. Because the image similarities among adjacent spectrum bands are different with the change of spectrum, the whole multispectral image sequence is partitioned into several subsets, and then DPCM predictors are designed separately for each image subset. After de-correlating spectral redundancy, a efficient wavelet coding method, SPIHT, is used to compress error images created by partitioning DPCM algorithm. The experimental results from simulated multispectral images and practical 64-band multispectral images have shown that the algorithm is fast, efficient and practical.