Abstract
Multispectral spatial data is to be found in several fields of image processing (e.g. Remote Sensing or Electron Microscopy). The acquisition process often generates “noisy” images such that the observed data may be viewed as a randomisation of the true or underlying information. Multivariate Kriging can be used to produce an optimal multivariate linear filtering of individual images. The method is illustrated by an application to microprobe X-ray images of superalloy microstructures, and is compared to the results obtained by the traditional moving average filter.
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© 1989 Springer Science+Business Media Dordrecht
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Daly, C., Jeulin, D., Lajaunie, C. (1989). Application of Multivariate Kriging to the Processing of Noisy Images. In: Armstrong, M. (eds) Geostatistics. Quantitative Geology and Geostatistics, vol 4. Springer, Dordrecht. https://doi.org/10.1007/978-94-015-6844-9_59
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DOI: https://doi.org/10.1007/978-94-015-6844-9_59
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