Title :
Adaptive comb-filtering using neural networks
Author :
Horn, Joachim ; Jansen, Michael ; Prange, Stefan J.
Author_Institution :
Corp. Technol., Siemens AG, Munich, Germany
fDate :
8/1/1997 12:00:00 AM
Abstract :
Neural networks of multi-layer perceptron type perform well as adaptive comb-filters for PAL and NTSC color decoding. They are optimized by learning algorithms. Sampled encoded and original images serve as training patterns
Keywords :
adaptive filters; adaptive signal processing; decoding; image sampling; multilayer perceptrons; nonlinear filters; optimisation; telecommunication standards; television standards; video coding; NTSC color decoding; PAL color decoding; adaptive comb-filtering; learning algorithms; multi-layer perceptron type; neural networks; nonlinear filtering; optimization; sampled encoded images; sampled original images; training patterns; video processing; Adaptive filters; Decoding; Filtering; Frequency; Multi-layer neural network; Multilayer perceptrons; Neural networks; Nonlinear filters; Power capacitors; Switches;
Journal_Title :
Consumer Electronics, IEEE Transactions on
