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Scattered Data Interpolation for Remote Sensing Applications

Erik Ringaby, Ola Friman, Per-Erik Forssén
Proceedings of SSBA 2013 IAPR
March 2013


In this paper we address the problem of accurate and efficient visualisation of data from a hyperspectral pushbroom sensor. Five different methods are compared on a dataset of irregularly sampled scan lines: nearest neighbour, splatting, natural neighbours, inverse distance weighted interpolation and local kriging. To compare these methods, a hyperspectral dataset acquired with a pushbroom sensor is divided into two parts by subsampling, where one part is used to reconstruct the surface texture on a regular grid, and the other one is used as a ground truth for the evaluation of the reconstruction.

Full Paper

This is a preliminary version of work published in the TIP journal.

Bibtex entry

  author = 	 {Erik Ringaby and Ola Friman and Per-Erik Forss\'en},
  title = 	 {Scattered Data Interpolation for Remote Sensing Applications},
  booktitle =    {Proceedings of {SSBA} 2013 {IAPR}},
  OPTpages = 	 {},
  month = 	 {March},
  year = 	 {2013},
  organization = {{IAPR}},
  note =         {Non-reviewed workshop},
  publisher =    {{SSBA}}

Per-Erik Forssén

Per-Erik Forssén


Computer Vision Laboratory
Department of Electrical Engineering
Building B
Room 2D:521
SE-581 83 Linköping, Sweden
+46(0)13 285654

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