### Abstract

The compression of LANDSAT images using Hilbert or Peano scanning and adaptive arithmetic coding is considered. The Hilbert scan is a general technique for continuous scanning of multidimensional data. Arithmetic coding has established itself as the superior method for lossless compression. This paper extends on previous work on the integration of the arithmetic coding methodology and an n-dimensional Hilbert scanning algorithm developed by Perez, Kamata and Kawaguchi. Hilbert scanning preserves the spatial continuity of an image, on both the x and y directions, and a higher correlation exists between continuous points than in a raster scan. Therefore, a Hilbert adaptive scheme can better estimate the local probability distributions. Arithmetic coding is most efficient when the probabilities of the symbols are close to one. Therefore, by integrating both the spatial and spectral information into a unified context a high rate of compression can be achieved.

Original language | English |
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Title of host publication | Proceedings of SPIE - The International Society for Optical Engineering |

Place of Publication | Bellingham, WA, United States |

Publisher | Publ by Int Soc for Optical Engineering |

Pages | 879-884 |

Number of pages | 6 |

Volume | 1605 |

Edition | pt 2 |

ISBN (Print) | 0819407429 |

Publication status | Published - 1991 |

Externally published | Yes |

Event | Visual Communications and Image Processing '91: Visual Communications Part 2 (of 2) - Boston, MA, USA Duration: 1991 Nov 11 → 1991 Nov 13 |

### Other

Other | Visual Communications and Image Processing '91: Visual Communications Part 2 (of 2) |
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City | Boston, MA, USA |

Period | 91/11/11 → 91/11/13 |

### Fingerprint

### ASJC Scopus subject areas

- Electrical and Electronic Engineering
- Condensed Matter Physics

### Cite this

*Proceedings of SPIE - The International Society for Optical Engineering*(pt 2 ed., Vol. 1605, pp. 879-884). Bellingham, WA, United States: Publ by Int Soc for Optical Engineering.

**Arithmetic coding model for compression of LANDSAT images.** / Perez, Arnulfo; Kamata, Seiichiro; Kawaguchi, Eiji.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*Proceedings of SPIE - The International Society for Optical Engineering.*pt 2 edn, vol. 1605, Publ by Int Soc for Optical Engineering, Bellingham, WA, United States, pp. 879-884, Visual Communications and Image Processing '91: Visual Communications Part 2 (of 2), Boston, MA, USA, 91/11/11.

}

TY - GEN

T1 - Arithmetic coding model for compression of LANDSAT images

AU - Perez, Arnulfo

AU - Kamata, Seiichiro

AU - Kawaguchi, Eiji

PY - 1991

Y1 - 1991

N2 - The compression of LANDSAT images using Hilbert or Peano scanning and adaptive arithmetic coding is considered. The Hilbert scan is a general technique for continuous scanning of multidimensional data. Arithmetic coding has established itself as the superior method for lossless compression. This paper extends on previous work on the integration of the arithmetic coding methodology and an n-dimensional Hilbert scanning algorithm developed by Perez, Kamata and Kawaguchi. Hilbert scanning preserves the spatial continuity of an image, on both the x and y directions, and a higher correlation exists between continuous points than in a raster scan. Therefore, a Hilbert adaptive scheme can better estimate the local probability distributions. Arithmetic coding is most efficient when the probabilities of the symbols are close to one. Therefore, by integrating both the spatial and spectral information into a unified context a high rate of compression can be achieved.

AB - The compression of LANDSAT images using Hilbert or Peano scanning and adaptive arithmetic coding is considered. The Hilbert scan is a general technique for continuous scanning of multidimensional data. Arithmetic coding has established itself as the superior method for lossless compression. This paper extends on previous work on the integration of the arithmetic coding methodology and an n-dimensional Hilbert scanning algorithm developed by Perez, Kamata and Kawaguchi. Hilbert scanning preserves the spatial continuity of an image, on both the x and y directions, and a higher correlation exists between continuous points than in a raster scan. Therefore, a Hilbert adaptive scheme can better estimate the local probability distributions. Arithmetic coding is most efficient when the probabilities of the symbols are close to one. Therefore, by integrating both the spatial and spectral information into a unified context a high rate of compression can be achieved.

UR - http://www.scopus.com/inward/record.url?scp=0026403819&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0026403819&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:0026403819

SN - 0819407429

VL - 1605

SP - 879

EP - 884

BT - Proceedings of SPIE - The International Society for Optical Engineering

PB - Publ by Int Soc for Optical Engineering

CY - Bellingham, WA, United States

ER -