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Implementation of Linear Prediction Models for Lossless Compression of Hyperspectral Images in Novel Parallel Environments

  • Jarno Mielikäinen
  • Pekka Toivanen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2749)

Abstract

This paper presents the implementation of a new method for lossless compression of hyperspectral images for novel parallel environments. The method in question is an interband version of the linear prediction approach for hyperspectral images. The interband linear prediction method consists of two stages: predictive decorrelation that produces residuals and the entropy coding of the residuals. The results and comparisons with other methods are discussed. The speedup of the thread version is almost linear with respect to the number of processors.

Keywords

Hyperspectral Image Linear Prediction Lossless Compression Entropy Code Parallel Environment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Jarno Mielikäinen
    • 1
  • Pekka Toivanen
    • 1
  1. 1.Lappeenranta University of TechnologyLappeenrantaFinland

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