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Clustered DPCM for the lossless compression of hyperspectral images

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2 Author(s)
J. Mielikainen ; Dept. of Inf. Technol., Lappeenranta Univ. of Technol., Finland ; P. Toivanen

A clustered differential pulse code modulation lossless compression method for hyperspectral images is presented. The spectra of a hyperspectral image is clustered, and an optimized predictor is calculated for each cluster. Prediction is performed using a linear predictor. After prediction, the difference between the predicted and original values is computed. The difference is entropy-coded using an adaptive entropy coder for each cluster. The achieved compression ratios presented here are compared with those of existing methods. The results show that the proposed lossless compression method for hyperspectral images outperforms previous methods.

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IEEE Transactions on Geoscience and Remote Sensing  (Volume:41 ,  Issue: 12 )