Lossless Compression of Hyperspectral Images Using Clustered Linear Prediction With Adaptive Prediction Length

被引:52
作者
Mielikainen, Jarno [1 ,2 ,3 ]
Huang, Bormin [1 ]
机构
[1] Univ Wisconsin, Ctr Space Sci & Engn, Madison, WI 53706 USA
[2] Univ Eastern Finland, Dept Comp Sci, Kuopio 70211, Finland
[3] Yonsei Univ, Sch Elect & Elect Engn, Seoul 120749, South Korea
基金
芬兰科学院;
关键词
Hyperspectral images; image compression; lossless compression;
D O I
10.1109/LGRS.2012.2191531
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
This letter explores the use of adaptive prediction length in clustered differential pulse code modulation (C-DPCM) lossless compression method for hyperspectral images. In the C-DPCM method, linear prediction is performed using coefficients optimized for each spectral cluster separately. The difference between the predicted and original values is entropy coded using an adaptive range coder for each cluster. The results show that the C-DPCM-with-adaptive-prediction-length method has lower bit-per-pixel value than the original C-DPCM method for Consultative Committee for Space Data Systems 2006 AVIRIS test images. Both calibrated and uncalibrated image compression results are improved by adaptive prediction length.
引用
收藏
页码:1118 / 1121
页数:4
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