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Another important novelty is that we use motion estimation reliabilities derived from both the depth and the luminance to derive coefficients for motion compensated filtering in wavelet domain.
A similar idea of multiframe motion compensated filtering, entirely in the pixel domain was first presented in [19].
The motion estimation step is followed by the wavelet decomposition step and by motion compensated filtering, which is performed in the wavelet domain, using a variable number of motion hypotheses (depending on their reliability) and data dependent weighted averaging.
Then, the algorithm performs motion compensated filtering which uses motion estimation reliabilities from the motion estimation step.
Similarly, the proposed motion compensated filtering does not add much overhead, since filtering weights are calculated during the motion estimation step.
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In particular, we use motion reliabilities derived from both depth and luminance as weighting factors for motion compensated temporal filtering.
The proposed design constraints are used within the motion compensated temporal filtering (MCTF) framework to demonstrate its advancement in robust peer-to-peer video streaming.
However, in [5], each description also has two parts, where both of them apply motion compensated temporal filter so the encoding complexity of the system is similar to the conventional inter-frame model.
The corrupted sites were then treated with a three-tap non-motion compensated median filter which removed C as outliers in the underlying observed sequence.
The forward motion estimation, the bilateral motion compensated interpolation and the motion vector correction techniques using weighted median filters are used to generate the side information.
Motion compensated prediction (MCP) implemented in most video coding schemes is based on translational motion model.
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