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Association for More Than Two Processes

In: Spatial Relationships Between Two Georeferenced Variables

Author

Listed:
  • Ronny Vallejos

    (Federico Santa María Technical University, Department of Mathematics)

  • Felipe Osorio

    (Federico Santa María Technical University, Department of Mathematics)

  • Moreno Bevilacqua

    (Universidad Adolfo Ibañez, Faculty of Engineering and Sciences)

Abstract

Addressing the spatial association between three or more processes is a challenging problem. Here, similarly as in the previous chapters we focus our attention in a continuous multivariate process with more than two components. Although motivation could be theoretical, there are several applications in the context of image processing. For instance, one could be interested in reducing the dimensionality of the spectral bands associated with a multispectral satellite image. Such dimensionality might be addressed considering the level of association among the image bands. In this chapter instead of working with the covariance function, this problem will be tackled considering a measure of the association between the processes that is an extension of the codispersion coefficient. As a consequence, we introduce a supervised maximum likelihood method of image classification, based on the selected image bands. An application with a real LANDSAT image will be used for illustrative purposes.

Suggested Citation

  • Ronny Vallejos & Felipe Osorio & Moreno Bevilacqua, 2020. "Association for More Than Two Processes," Springer Books, in: Spatial Relationships Between Two Georeferenced Variables, chapter 0, pages 131-144, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-56681-4_7
    DOI: 10.1007/978-3-030-56681-4_7
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