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Splines Interpolation in High Resolution Satellite Imagery

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Advances in Visual Computing (ISVC 2005)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 3804))

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Abstract

In this paper some insights into the behavior of interpolation functions for resampling high resolution satellite images are presented. Using spatial and frequency domain characteristics, splines interpolation performance is compared to nearest-neighbor, linear and cubic interpolation. It is shown that splines interpolation injects spatial information into the final resample image better than the other three methods. Splines interpolation is also shown to be faster than cubic interpolation when the former is implemented with the LU decomposition algorithm for its tridiagonal system of linear equations. Therefore, if the main purpose for high resolution satellite resampling is to obtain an optimal smooth final image, intuitive and experimental justifications are provided for preferring splines interpolation to nearest-neighbor, linear and cubic interpolation.

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Author information

Authors and Affiliations

  1. Departamento de Matemáticas, Universidad de Alcalá, 28871, Madrid, Spain

    José A. Malpica

Authors
  1. José A. Malpica
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, University of Nevada, Reno, USA

    George Bebis

  2. NASA Ames Research Center, Moffett Field, CA, USA

    Richard Boyle

  3. Desert Research Institute, Reno, NV, USA

    Darko Koracin

  4. Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    Bahram Parvin

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© 2005 Springer-Verlag Berlin Heidelberg

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Malpica, J.A. (2005). Splines Interpolation in High Resolution Satellite Imagery. In: Bebis, G., Boyle, R., Koracin, D., Parvin, B. (eds) Advances in Visual Computing. ISVC 2005. Lecture Notes in Computer Science, vol 3804. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11595755_68

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  • DOI: https://doi.org/10.1007/11595755_68

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-30750-1

  • Online ISBN: 978-3-540-32284-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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