Abstract

In this letter a new algorithm for lossless compression of hyperspectral images using hybrid context prediction is proposed. Lossless compression algorithms are typically divided into two stages, a decorrelation stage and a coding stage. The decorrelation stage supports both intraband and interband predictions. The intraband (spatial) prediction uses the median prediction model, since the median predictor is fast and efficient. The interband prediction uses hybrid context prediction. The hybrid context prediction is the combination of a linear prediction (LP) and a context prediction. Finally, the residual image of hybrid context prediction is coded by the arithmetic coding. We compare the proposed lossless compression algorithm with some of the existing algorithms for hyperspectral images such as 3D-CALIC, M-CALIC, LUT, LAIS-LUT, LUT-NN, DPCM (C-DPCM), JPEG-LS. The performance of the proposed lossless compression algorithm is evaluated. Simulation results show that our algorithm achieves high compression ratios with low complexity and computational cost.

© 2012 OSA

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  1. B. Aiazzi, L. Alparone, and S. Baronti, “Near-lossless image compression by relaxation-labeled prediction,” Signal Process. 82(11), 1619–1631 (2002).
    [CrossRef]
  2. E. Magli, G. Olmo, and E. Quacchio, “Optimized onboard lossless and near-lossless compression of hyperspectral data using CALIC,” IEEE Geosci. Remote Sens. Lett. 1(1), 21–25 (2004).
    [CrossRef]
  3. B. Aiazzi, S. Baronti, and L. Alparone, “Lossless compression of hyperspectral images using multiband lookup tables,” IEEE Signal Process. Lett. 16(6), 481–484 (2009).
    [CrossRef]
  4. J. Mielikainen, “Lossless compression of hyperspectral images using lookup tables,” IEEE Signal Process. Lett. 13(3), 157–160 (2006).
    [CrossRef]
  5. B. Huang and Y. Sriraja, “Lossless compression of hyperspectral imagery via lookup tables with predictor selection,” Proc. SPIE 6365, 63650L, 63650L-8 (2006).
    [CrossRef]
  6. X. Tang, W. Pearlman, and J. Modestino, ““Hyperspectral image compression using three-dimensional wavelet coding,” Proc.SPIE/IS&T Electron, Imaging 1, 1037–1047 (2003).
  7. B. Penna, T. Tillo, E. Magli, and G. Olmo, “Progressive 3-D coding of hyperspectral images based on JPEG 2000,” IEEE Geosci. Remote Sens. Lett. 3(1), 125–129 (2006).
    [CrossRef]
  8. J. Zhang and G. Liu, “An efficient reordering prediction-based lossless compression algorithm for hyperspectral images,” IEEE Geosci. Remote Sens. Lett. 4(2), 283–287 (2007).
    [CrossRef]
  9. M. J. Weinberger, G. Seroussi, and G. Sapiro, “The LOCO-I lossless image compression algorithm: principles and standardization into JPEG-LS,” IEEE Trans. Image Process. 9(8), 1309–1324 (2000).
    [CrossRef] [PubMed]
  10. J. S. Mielikainen, A. Kaarna, and P. Toivanen, “Lossless hyperspectral image compression via linear prediction,” Proc. SPIE 4725(8), 600–608 (2002).
    [CrossRef]
  11. F. Rizzo, B. Carpentieri, G. Motta, and J. A. Storer, “Low-complexity lossless compression of hyperspectral imagery via linear prediction,” IEEE Signal Process. Lett. 12(2), 138–141 (2005).
    [CrossRef]

2009 (1)

B. Aiazzi, S. Baronti, and L. Alparone, “Lossless compression of hyperspectral images using multiband lookup tables,” IEEE Signal Process. Lett. 16(6), 481–484 (2009).
[CrossRef]

2007 (1)

J. Zhang and G. Liu, “An efficient reordering prediction-based lossless compression algorithm for hyperspectral images,” IEEE Geosci. Remote Sens. Lett. 4(2), 283–287 (2007).
[CrossRef]

2006 (3)

J. Mielikainen, “Lossless compression of hyperspectral images using lookup tables,” IEEE Signal Process. Lett. 13(3), 157–160 (2006).
[CrossRef]

B. Huang and Y. Sriraja, “Lossless compression of hyperspectral imagery via lookup tables with predictor selection,” Proc. SPIE 6365, 63650L, 63650L-8 (2006).
[CrossRef]

B. Penna, T. Tillo, E. Magli, and G. Olmo, “Progressive 3-D coding of hyperspectral images based on JPEG 2000,” IEEE Geosci. Remote Sens. Lett. 3(1), 125–129 (2006).
[CrossRef]

2005 (1)

F. Rizzo, B. Carpentieri, G. Motta, and J. A. Storer, “Low-complexity lossless compression of hyperspectral imagery via linear prediction,” IEEE Signal Process. Lett. 12(2), 138–141 (2005).
[CrossRef]

2004 (1)

E. Magli, G. Olmo, and E. Quacchio, “Optimized onboard lossless and near-lossless compression of hyperspectral data using CALIC,” IEEE Geosci. Remote Sens. Lett. 1(1), 21–25 (2004).
[CrossRef]

2003 (1)

X. Tang, W. Pearlman, and J. Modestino, ““Hyperspectral image compression using three-dimensional wavelet coding,” Proc.SPIE/IS&T Electron, Imaging 1, 1037–1047 (2003).

2002 (2)

B. Aiazzi, L. Alparone, and S. Baronti, “Near-lossless image compression by relaxation-labeled prediction,” Signal Process. 82(11), 1619–1631 (2002).
[CrossRef]

J. S. Mielikainen, A. Kaarna, and P. Toivanen, “Lossless hyperspectral image compression via linear prediction,” Proc. SPIE 4725(8), 600–608 (2002).
[CrossRef]

2000 (1)

M. J. Weinberger, G. Seroussi, and G. Sapiro, “The LOCO-I lossless image compression algorithm: principles and standardization into JPEG-LS,” IEEE Trans. Image Process. 9(8), 1309–1324 (2000).
[CrossRef] [PubMed]

Aiazzi, B.

B. Aiazzi, S. Baronti, and L. Alparone, “Lossless compression of hyperspectral images using multiband lookup tables,” IEEE Signal Process. Lett. 16(6), 481–484 (2009).
[CrossRef]

B. Aiazzi, L. Alparone, and S. Baronti, “Near-lossless image compression by relaxation-labeled prediction,” Signal Process. 82(11), 1619–1631 (2002).
[CrossRef]

Alparone, L.

B. Aiazzi, S. Baronti, and L. Alparone, “Lossless compression of hyperspectral images using multiband lookup tables,” IEEE Signal Process. Lett. 16(6), 481–484 (2009).
[CrossRef]

B. Aiazzi, L. Alparone, and S. Baronti, “Near-lossless image compression by relaxation-labeled prediction,” Signal Process. 82(11), 1619–1631 (2002).
[CrossRef]

Baronti, S.

B. Aiazzi, S. Baronti, and L. Alparone, “Lossless compression of hyperspectral images using multiband lookup tables,” IEEE Signal Process. Lett. 16(6), 481–484 (2009).
[CrossRef]

B. Aiazzi, L. Alparone, and S. Baronti, “Near-lossless image compression by relaxation-labeled prediction,” Signal Process. 82(11), 1619–1631 (2002).
[CrossRef]

Carpentieri, B.

F. Rizzo, B. Carpentieri, G. Motta, and J. A. Storer, “Low-complexity lossless compression of hyperspectral imagery via linear prediction,” IEEE Signal Process. Lett. 12(2), 138–141 (2005).
[CrossRef]

Huang, B.

B. Huang and Y. Sriraja, “Lossless compression of hyperspectral imagery via lookup tables with predictor selection,” Proc. SPIE 6365, 63650L, 63650L-8 (2006).
[CrossRef]

Kaarna, A.

J. S. Mielikainen, A. Kaarna, and P. Toivanen, “Lossless hyperspectral image compression via linear prediction,” Proc. SPIE 4725(8), 600–608 (2002).
[CrossRef]

Liu, G.

J. Zhang and G. Liu, “An efficient reordering prediction-based lossless compression algorithm for hyperspectral images,” IEEE Geosci. Remote Sens. Lett. 4(2), 283–287 (2007).
[CrossRef]

Magli, E.

B. Penna, T. Tillo, E. Magli, and G. Olmo, “Progressive 3-D coding of hyperspectral images based on JPEG 2000,” IEEE Geosci. Remote Sens. Lett. 3(1), 125–129 (2006).
[CrossRef]

E. Magli, G. Olmo, and E. Quacchio, “Optimized onboard lossless and near-lossless compression of hyperspectral data using CALIC,” IEEE Geosci. Remote Sens. Lett. 1(1), 21–25 (2004).
[CrossRef]

Mielikainen, J.

J. Mielikainen, “Lossless compression of hyperspectral images using lookup tables,” IEEE Signal Process. Lett. 13(3), 157–160 (2006).
[CrossRef]

Mielikainen, J. S.

J. S. Mielikainen, A. Kaarna, and P. Toivanen, “Lossless hyperspectral image compression via linear prediction,” Proc. SPIE 4725(8), 600–608 (2002).
[CrossRef]

Modestino, J.

X. Tang, W. Pearlman, and J. Modestino, ““Hyperspectral image compression using three-dimensional wavelet coding,” Proc.SPIE/IS&T Electron, Imaging 1, 1037–1047 (2003).

Motta, G.

F. Rizzo, B. Carpentieri, G. Motta, and J. A. Storer, “Low-complexity lossless compression of hyperspectral imagery via linear prediction,” IEEE Signal Process. Lett. 12(2), 138–141 (2005).
[CrossRef]

Olmo, G.

B. Penna, T. Tillo, E. Magli, and G. Olmo, “Progressive 3-D coding of hyperspectral images based on JPEG 2000,” IEEE Geosci. Remote Sens. Lett. 3(1), 125–129 (2006).
[CrossRef]

E. Magli, G. Olmo, and E. Quacchio, “Optimized onboard lossless and near-lossless compression of hyperspectral data using CALIC,” IEEE Geosci. Remote Sens. Lett. 1(1), 21–25 (2004).
[CrossRef]

Pearlman, W.

X. Tang, W. Pearlman, and J. Modestino, ““Hyperspectral image compression using three-dimensional wavelet coding,” Proc.SPIE/IS&T Electron, Imaging 1, 1037–1047 (2003).

Penna, B.

B. Penna, T. Tillo, E. Magli, and G. Olmo, “Progressive 3-D coding of hyperspectral images based on JPEG 2000,” IEEE Geosci. Remote Sens. Lett. 3(1), 125–129 (2006).
[CrossRef]

Quacchio, E.

E. Magli, G. Olmo, and E. Quacchio, “Optimized onboard lossless and near-lossless compression of hyperspectral data using CALIC,” IEEE Geosci. Remote Sens. Lett. 1(1), 21–25 (2004).
[CrossRef]

Rizzo, F.

F. Rizzo, B. Carpentieri, G. Motta, and J. A. Storer, “Low-complexity lossless compression of hyperspectral imagery via linear prediction,” IEEE Signal Process. Lett. 12(2), 138–141 (2005).
[CrossRef]

Sapiro, G.

M. J. Weinberger, G. Seroussi, and G. Sapiro, “The LOCO-I lossless image compression algorithm: principles and standardization into JPEG-LS,” IEEE Trans. Image Process. 9(8), 1309–1324 (2000).
[CrossRef] [PubMed]

Seroussi, G.

M. J. Weinberger, G. Seroussi, and G. Sapiro, “The LOCO-I lossless image compression algorithm: principles and standardization into JPEG-LS,” IEEE Trans. Image Process. 9(8), 1309–1324 (2000).
[CrossRef] [PubMed]

Sriraja, Y.

B. Huang and Y. Sriraja, “Lossless compression of hyperspectral imagery via lookup tables with predictor selection,” Proc. SPIE 6365, 63650L, 63650L-8 (2006).
[CrossRef]

Storer, J. A.

F. Rizzo, B. Carpentieri, G. Motta, and J. A. Storer, “Low-complexity lossless compression of hyperspectral imagery via linear prediction,” IEEE Signal Process. Lett. 12(2), 138–141 (2005).
[CrossRef]

Tang, X.

X. Tang, W. Pearlman, and J. Modestino, ““Hyperspectral image compression using three-dimensional wavelet coding,” Proc.SPIE/IS&T Electron, Imaging 1, 1037–1047 (2003).

Tillo, T.

B. Penna, T. Tillo, E. Magli, and G. Olmo, “Progressive 3-D coding of hyperspectral images based on JPEG 2000,” IEEE Geosci. Remote Sens. Lett. 3(1), 125–129 (2006).
[CrossRef]

Toivanen, P.

J. S. Mielikainen, A. Kaarna, and P. Toivanen, “Lossless hyperspectral image compression via linear prediction,” Proc. SPIE 4725(8), 600–608 (2002).
[CrossRef]

Weinberger, M. J.

M. J. Weinberger, G. Seroussi, and G. Sapiro, “The LOCO-I lossless image compression algorithm: principles and standardization into JPEG-LS,” IEEE Trans. Image Process. 9(8), 1309–1324 (2000).
[CrossRef] [PubMed]

Zhang, J.

J. Zhang and G. Liu, “An efficient reordering prediction-based lossless compression algorithm for hyperspectral images,” IEEE Geosci. Remote Sens. Lett. 4(2), 283–287 (2007).
[CrossRef]

IEEE Geosci. Remote Sens. Lett. (3)

E. Magli, G. Olmo, and E. Quacchio, “Optimized onboard lossless and near-lossless compression of hyperspectral data using CALIC,” IEEE Geosci. Remote Sens. Lett. 1(1), 21–25 (2004).
[CrossRef]

B. Penna, T. Tillo, E. Magli, and G. Olmo, “Progressive 3-D coding of hyperspectral images based on JPEG 2000,” IEEE Geosci. Remote Sens. Lett. 3(1), 125–129 (2006).
[CrossRef]

J. Zhang and G. Liu, “An efficient reordering prediction-based lossless compression algorithm for hyperspectral images,” IEEE Geosci. Remote Sens. Lett. 4(2), 283–287 (2007).
[CrossRef]

IEEE Signal Process. Lett. (3)

B. Aiazzi, S. Baronti, and L. Alparone, “Lossless compression of hyperspectral images using multiband lookup tables,” IEEE Signal Process. Lett. 16(6), 481–484 (2009).
[CrossRef]

J. Mielikainen, “Lossless compression of hyperspectral images using lookup tables,” IEEE Signal Process. Lett. 13(3), 157–160 (2006).
[CrossRef]

F. Rizzo, B. Carpentieri, G. Motta, and J. A. Storer, “Low-complexity lossless compression of hyperspectral imagery via linear prediction,” IEEE Signal Process. Lett. 12(2), 138–141 (2005).
[CrossRef]

IEEE Trans. Image Process. (1)

M. J. Weinberger, G. Seroussi, and G. Sapiro, “The LOCO-I lossless image compression algorithm: principles and standardization into JPEG-LS,” IEEE Trans. Image Process. 9(8), 1309–1324 (2000).
[CrossRef] [PubMed]

Proc. SPIE (2)

J. S. Mielikainen, A. Kaarna, and P. Toivanen, “Lossless hyperspectral image compression via linear prediction,” Proc. SPIE 4725(8), 600–608 (2002).
[CrossRef]

B. Huang and Y. Sriraja, “Lossless compression of hyperspectral imagery via lookup tables with predictor selection,” Proc. SPIE 6365, 63650L, 63650L-8 (2006).
[CrossRef]

Proc.SPIE/IS&T Electron, Imaging (1)

X. Tang, W. Pearlman, and J. Modestino, ““Hyperspectral image compression using three-dimensional wavelet coding,” Proc.SPIE/IS&T Electron, Imaging 1, 1037–1047 (2003).

Signal Process. (1)

B. Aiazzi, L. Alparone, and S. Baronti, “Near-lossless image compression by relaxation-labeled prediction,” Signal Process. 82(11), 1619–1631 (2002).
[CrossRef]

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