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《Journal of Jilin University(Information Science Edition)》 2009-03
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Hyperspectral Image Lossless Compression Algorithm Based on Bidirectional Interband Prediction

WANG Lang,GUO Shu-xu(College of Electronic Science and Engineering,Jilin University,Changchun 130012,China)  
To improve the real-time performance of the current compression algorithms on hyperspectral image,a new lossless compression method based on prediction tree with error variances compensated for hyperspectral image is proposed.The method incorporates prediction tree and adaptive interband prediction techniques.The bidirectional interband prediction to current band is applied to hyperspectral image compression.The error created by prediction tree is compensated by linear adaptive predictor which de-correlates spectral statistic redundancy.In consideration of the complexity for the coefficients' calculation,a correlation-driven adaptive estimator is designed with which parameters are uniquely determined by the previously coded pixels.After de-correlating intraband and interband redundancy,an efficient wavelet coding method,SPIHT(Set Partitioning in Hierarchical Trees),is used to encode residual image.The experiments show that the proposed method achieves both low overhead and high compression ratio in comparison with the popular lossless compression algorithm.
【CateGory Index】: TP751
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【References】
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【Co-citations】
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1 Xia Hao Zhang Rong (Information Processing Center, University of Science & Technology of China, Hefei 230027, China);The Lossless Compression Method for Hyperspectral Images Based on Optimized Prediction Tree[J];Journal of Electronics & Information Technology;2009-04
2 Huo Cheng-fu Zhang Rong(Department of Electronic Engineering and Information Science,University of Science and Technology of China,Hefei 230027,China);Lossless Compression Based on Searching the Optimal Couple Prediction Wavebands for Hyperspectral Image[J];Journal of Electronics & Information Technology;2009-05
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