Title :
The outlier process [picture processing]
Author :
Geiger, Davi ; Pereira, Ricardo Alberto Marques
Author_Institution :
Siemens Corp. Res. Inc., Princeton, NJ, USA
fDate :
30 Sep-1 Oct 1991
Abstract :
The authors discuss the problem of detecting outliers from a set of surface data. They start from the Bayes approach and the assumption that surfaces are piecewise smooth and corrupted by a combination of white Gaussian and salt and pepper noise. They show that such surfaces can be modelled by introducing an outlier process that is capable of `throwing away´ data. They make use of mean field techniques to finally obtain a deterministic network. The experimental results with real images support the model
Keywords :
Bayes methods; image reconstruction; white noise; Bayes approach; Gaussian noise; deterministic network; mean field techniques; outliers detection; picture processing; salt and pepper noise; surface data; surface reconstruction; Biomembranes; Costs; Educational institutions; Face detection; Gaussian noise; Image processing; Image reconstruction; Lattices; Markov random fields; Surface reconstruction;
Conference_Titel :
Neural Networks for Signal Processing [1991]., Proceedings of the 1991 IEEE Workshop
Conference_Location :
Princeton, NJ
Print_ISBN :
0-7803-0118-8
DOI :
10.1109/NNSP.1991.239535
