Two-dimensional frequency domain motion compensation for spatiotemporal signals

Signals, Systems and Computers, 1995. 1995 Conference Record of the Twenty-Ninth Asilomar Conference(1995)

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摘要
Motion compensation has been widely used in video signal compression to reduce the redundancy among successive frames. A two-dimensional (2-D), frequency domain (F-D), motion compensation technique is developed which employs adaptive system modeling and exploits both spatial and temporal redundancies. Here, motion competition is accomplished by using two optimal predictors designed in the 2-D F-D. The predictors are characterized by their coefficient which are adaptively updated for every frame. Two implementation schemes, forward and backward, are proposed and successfully applied to both video signal and the 2-D wavelet transform coefficients of the video signals. The proposed 2-D F-D linear prediction approach is computationally comparable, but has several important advantages over existing spatial block matching methods such as improving the compensation efficiency by controlling the predictor order. Also, the technique presented is applicable for motion compensation under more general conditions, namely, spatial shift, rotation and scaling. For illustration, simulation results are given to show the performance of the proposed technique.
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关键词
video signal compression,simulation results,motion compensation,spatial block matching methods,redundancy reduction,spatiotemporal signals,backward compensation,wavelet transforms,adaptive system modeling,2d wavelet transform coefficients,adaptive signal processing,spatiotemporal signal,scaling,compensation efficiency,frequency-domain analysis,data compression,rotation,two-dimensional frequency domain,spatial shift,spatial redundancy,optimal predictors,predictor order control,forward compensation,video coding,2d frequency domain motion compensation,prediction theory,temporal redundancy,predictor coefficient,two-dimensional frequency domain motion,performance,2d frequency-domain linear prediction,wavelet transform,frequency domain analysis,frequency domain,adaptive system
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