@incollection{derigoMultidimensionalWeightedMedian2012,
  title = {Multi-Dimensional Weighted Median: The Module "Wmedian" of the {{Mastrave}} Modelling Library},
  booktitle = {Semantic {{Array Programming}} with {{Mastrave}} - {{Introduction}} to {{Semantic Computational Modelling}}},
  author = {{de Rigo}, Daniele},
  year = {2012},
  publisher = {{Mastrave project}},
  abstract = {Weighted median (WM) filtering is a well known technique for dealing with noisy images and a variety of WM-based algorithms have been proposed as effective ways for reducing uncertainties or reconstructing degraded signals by means of available information with heterogeneous reliability. Here a generalized module for applying weighted median filtering to multi-dimensional arrays of information with associated multi-dimensional arrays of corresponding weights is presented. Weights may be associated to single elements or to groups of elements along given dimensions of the multi-dimensional arrays. The filtered information derives from a reduction operator applied along a custom dimension.},
  keywords = {*imported-from-citeulike-INRMM,~INRMM-MiD:c-14257128,computational-science,free-scientific-software,free-software,gnu-octave,integration-techniques,mastrave-modelling-library,median,modelling,robust-modelling,semantic-array-programming,semantics,semap,software-engineering,uncertainty,weighting},
  lccn = {INRMM-MiD:c-14257128}
}

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