A Neural LUM Smoother
In this paper a design of neural LUM smoother is presented. The LUM smoother distinguishes by a number of smoothing characteristics done by the filter parameter. However, the tuning parameter for smoothing is fixed for whole image. The new method realizes adaptive control of the level of smoothing by neural networks. The well-known and very popular backpropagation algorithm is used. The analysis of the proposed methods is evaluated through subjective and objective criteria and compared with the traditional LUM smoother.
KeywordsLUM filters, neural networks, backpropagation, impulsive noise, smoothing, adaptive control
Document typePeer reviewed
Document versionFinal PDF
SourceRadioengineering. 2000, vol. 9, č. 3, s. 5-7. ISSN 1210-2512
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