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However, as the difference of the prediction gain between consecutive frames becomes larger, artifacts become more severe.
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In interframe coding, motion estimation and compensation have become powerful techniques to eliminate the temporal redundancy due to high correlation between consecutive frames [1].
Traditional FGS rate control techniques lack a systematic approach to making tradeoffs between image quality, motion smoothness (i.e., the frame rate), and video smoothness (PSNR difference between consecutive frames), according to limitations on system resources and users' preferences.
Additionally, small local motions between consecutive frames are estimated using block matching procedure in different directions, gathering interframe samples with similar features for efficient denoising.
Block-based motion estimation plays a significant role in video codecs by exploiting and reducing the temporal redundancies that exist between consecutive frames in a video sequence.
Processing is performed for a motion differentiating between consecutive frames.
Note that the detection-based tracking is only carried out between consecutive frames.
This shows the amount of change occurring between consecutive frames, which is shown in Fig. 6.
Event segmentation is carried out by computing optical flow between consecutive frames of the video.
Unlike image segmentation, video segmentation can exploit temporal coherence between consecutive frames.
However, correlation between consecutive frames is often neither spatially nor temporally stationary.
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