Motion compensated interpolation (MCI) refers to the process of taking a video sequence, finding motion information, and then using that information to produce interpolated video frames between source frames. In this study, we compare two MCI techniques: adjacent-frame motion compensated interpolation (AF-MCI) and wide-span motion compensated interpolation (WS-MCI). Using reproducible artificially generated video sequences, the methods are quantitatively compared with the objective of optimizing interpolated frame quality relative to control interpolated frames. This is useful because on a large flat-panel display with high resolution (such as HDTV), frame transition coherence becomes a crucial factor in assessing the quality of the user's viewing experience. To enhance MCI, the encoder should attempt to exploit long-term statistical dependencies, precisely estimate motion by modeling the motion vector field, and superimpose efficient prediction/interpolation algorithms. WS-MCI achieves this. Computer simulations using artificially generated video sequences demonstrate the consistent advantage of WS-MCI over adjacent-frame MCI under increasingly complex source scenes and chaotic occlusion conditions.
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