A Neural LUM Smoother
Alternativní metriky PlumXhttp://hdl.handle.net/11012/58232
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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.
Zdrojový dokumentRadioengineering. 2000, vol. 9, č. 3, s. 5-7. ISSN 1210-2512
- 2000/3