一种结合整型最佳谱间预测与SPIHT的MODIS影像无损压缩算法

针对MODIS(Moderate Resolution Imaging Spectroradiometer)影像数据海量并具有重要研究价值的特点,研究MODIS影像的无损压缩算法。采用最佳线性预测方法,通过波段相关性排序确定波段最优预测顺序,并自适应计算"预测波段"与"当前波段"的二阶最佳预测器系数,减少谱间冗余;以多级树集合分裂树(Set Partitioning In Hierarchical Trees,SPIHT)编码算法降低谱内相关。为确保无损压缩,对线性预测系数进行最佳逼近取整操作,并采用基于提升格式的D5/3整数小波变换。实验结果表明本文提出的算法在压缩比上性能较3DSPIHT等算法突出。

Lossless compression of MODIS image based on optimal integer prediction of inter-band and SPIHT algorithm

The enormous volumes and valuable applications of MODIS (Moderate Resolution Imaging Spectroradiometer) multi-spectral images make it need to be compressed losslessly with effective method. To solve this problem, the optimal linear prediction and band ordering are adopted here to exploit abundant spectral redundancy, lifting wavelet transform and SPIHT algorithm are used to eliminate the spatial redundancy of MODIS data. The optimal inter-band prediction sequence is specified by band ordering, and except the first band, only residual error images of other bands need to be encoded after band prediction. To avoid information loss, the optimal linear predictor is improved by rounding the prediction coefficients into integers, and D5/3 lifting wavelet is used to implement integer-to-integer wavelet transform of the band image, which also accelerate the compression. Finally, some lossless compression methods such as "3DSPIHT" are compared with this compression method, and the experimental results show that our method has more compression capability.