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A study on motion prediction and subband coding of moving pictuers using GRNN  

Han, Young-Oh (남서울대학교 전자공학과)
Publication Information
The Journal of the Korea institute of electronic communication sciences / v.5, no.3, 2010 , pp. 256-261 More about this Journal
Abstract
In this paper, a new nonlinear predictor using general regression neural network(GRNN) is proposed for the subband coding of moving pictures. The performance of a proposed nonlinear predictor is compared with BMA(Block Match Algorithm), the most conventional motion estimation technique. As a result, the nonlinear predictor using GRNN can predict well more 2-3dB than BMA. Specially, because of having a clustering process and smoothing noise signals, this predictor well preserves edges in frames after predicting the subband signal. This result is important with respect of human visual system and is excellent performance for the subband coding of moving pictures.
Keywords
GRNN; BMA; subband coding; nonlinear predictor;
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