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access icon free Lossless compression of hyperspectral imagery via RLS filter

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References

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      • 1. Duan, H., Fang, Y., Huang, B.: ‘Parallel design of JPEG-LS encoder on graphics processing units’, J. Appl. Remote Sens., 2012, 6, pp. 061508-1061508-13 (doi: 10.1117/1.JRS.6.061508).
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      • 4. Mielikainen, J., Toivanen, P.: ‘Lossless compression of hyperspectral images using a quantized index to lookup tables’, IEEE Geosci. Remote Sens. Lett., 2008, 5, (3), pp. 474478 (doi: 10.1109/LGRS.2008.917598).
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      • 3. Mielikainen, J., Huang, B.: ‘Lossless compression of hyperspectral images using clustered linear prediction with adaptive prediction length’, IEEE Geosci. Remote Sens. Lett., 2012, 9, (6), pp. 11181121 (doi: 10.1109/LGRS.2012.2191531).
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      • 2. Sanchez, J., Auge, E., Santalo, J., Blanes, I., Serra-Sagrista, J., Kiely, A.: ‘Review and implementation of the emerging CCSDS Recommended Standard for Multispectral and Hyperspectral Lossless Image Coding’. 2011 1st Int. Conf. Data Compression, Communications and Processing, Palinuro, Italy, June 2011, pp. 224228.
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      • 5. CCSDS: ‘Lossless multispectral and hyperspectral image compression’, 123.0-B-1, CCSDS, 2012.
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      • 6. Lin, C., Huang, Y.: ‘An efficient lossless compression scheme for hyperspectral images using two-stage prediction’, IEEE Geosci. Remote Sens. Lett., 2010, 7, (3), pp. 558562 (doi: 10.1109/LGRS.2010.2041630).
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      • 7. Haykin, S.: ‘Adaptive filter theory’ (House of Electronics Industry, Beijing, 2010, 4th edn).
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