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On Generalized Separation and the Speedup of Local Operators on Multi-dimensional Signals



Sebastian Pfeiffer
Michael Mai
Wolfgang Globke
Jan Calliess


International Workshop on Multidimensional Systems, 2009.


International Workshop on Multidimensional Systems (nDS), Thessaloniki, 29. Juni - 1. Juli 2009

Along with the boom of computer vision- and other signal processing-based applications, the question of fast local operator application has become increasingly important over the past decade. For two-dimensional signals, such as images, local operator separation has proven to ameliorate the computational effort incurred by prominent operators such as mean filter, binomial filter or Sobel filter. However, many modern days' applications involve higher-dimensional input signals including tomography, functional magnetic resonance imaging (fMRI), selective plane illumination microscopy (SPIM), confocal laser scanning microscopy (CLSM), special image fusion.