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Backward and forward linear prediction applied to ultraspectral image processing

Effects on rate–distortion

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Abstract

Atmospheric infrared sounder images are ultraspectral data cubes that comprise over two thousand spectral bands accounting for well over 25 megapixels of information. In this paper, we focus on the analysis of backward and forward linear prediction (LP) applied in the context of ultraspectral image compression. We start by introducing a detailed analysis of the differences and similarities between them and proceed to present a mathematical model that integrates not only error signal but also LP coefficient encoding. In addition, to overcome some of the limitations of backward LP, we present a hybrid LP scheme where both, backward and forward LP, are put into consideration by dynamically interleaving them in order to minimize the mean square error of the error signal. The model is further extended to compare all three techniques, and both experimental and theoretical samples are contrasted to verify that hybrid LP provides most efficient compression method.

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Authors and Affiliations

  1. Meteorology Division, Ecotronics Ventures LLC, 12662 Piedmont Trail Road, Clarksburg, MD, 20871-4306, USA

    Rolando Herrero

  2. Electrical and Computer Engineering Department, Northeastern University, 360 Huntington Avenue, Boston, MA, 02115-5000, USA

    Vinay K. Ingle

Authors
  1. Rolando Herrero
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  2. Vinay K. Ingle
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Correspondence to Rolando Herrero.

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Herrero, R., Ingle, V.K. Backward and forward linear prediction applied to ultraspectral image processing. SIViP 10, 639–646 (2016). https://doi.org/10.1007/s11760-015-0788-y

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  • DOI: https://doi.org/10.1007/s11760-015-0788-y

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