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Proposes a fast local motion-compensation algorithm that improves motion-compensation performance for video sequences with brightness variations. The brightness variation parameters, a multiplier and an offset field for image intensity, are robustly estimated and local motions are compensated. We also propose the frame classification method based on the cross entropy between histograms of two successive frames, to detect the frame with brightness variations. Simulation results show that the proposed method yields a higher peak signal-to-noise ratio than the conventional methods, with a low computational load, when the video scene contains large brightness changes.
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Kim et al. (2003) studied this question.
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