一种结合整型最佳谱间预测与SPIHT的MODIS影像无损压缩算法
Lossless Compression of MODIS Image Based on Optimal Integer Prediction of Inter-band and SPIHT Algorithm
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摘要: 针对MODIS影像数据海量并具有重要研究价值的特点,研究了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的顺序,并自适应计算预测波段与当前波段的最佳预测器系数,减少谱间冗余;以多级树集合分裂(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,该算法在压缩比上的性能较3DSPIHT等算法突出。Abstract: The enormous volumes and valuable applications of MODIS multi-spectral images make it necessary to be compressed losslessly with effective methods.To solve this problem,an optimal linear prediction and band ordering are adopted to exploit abundant spectral redundancy,and SPIHT algorithm is used to eliminate the spatial redundancy of MODIS data.The optimal inter-band prediction sequence is specified by band ordering.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.The experimental results show that our method has more compression capabilities.