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《Laser Journal》 2016-02
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Lossless Compression of Hyper-spectral Image Based on Prediction

Yang Ming-long;College of land and resources engineering,Kunming University of Science and Technology;  
Hyper-spectral images have the characteristics of huge data,which have adverse effects on storage and transmission,In order to speed up the transmission speed and save the storage space,a new lossless compression algorithm based on the prediction for hyperspectral image is proposed.First of all,the current situation of the research on lossless compression of hyperspectral image is analyzed,and the existing problems in current lossless compression algorithm are found,and then the spatial correlation and spectral correlation of hyperspectral image are estimated to design a hyper-spectral image compression predictor,finally the test results show that the proposed algorithm can achieve the lossless compression of hyper-spectral image,compression effect is significantly better than current classical compression algorithms.
【Fund】: 教育部高校硕士点基金(200801120007)
【CateGory Index】: TP391.41
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