Multi-Dimensional Weighted Median: The Module "Wmedian" of the Mastrave Modelling Library. de Rigo, D. In Semantic Array Programming with Mastrave - Introduction to Semantic Computational Modelling. Mastrave project.
Multi-Dimensional Weighted Median: The Module "Wmedian" of the Mastrave Modelling Library [link]Paper  abstract   bibtex   
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.
@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},
  date = {2012},
  publisher = {{Mastrave project}},
  url = {http://mfkp.org/INRMM/article/14257128},
  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},
  options = {useprefix=true}
}
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