Sentence examples for temporal predictor from inspiring English sources
Namely, when the SAD, based on which the motion vector associated with temporal predictor r k, u n was determined, is not smaller than a certain threshold T, the motion vector and associated temporal predictor is labeled as unreliable.
After the execution of the OBME, a temporal predictor block R k, u n for every block Y u n has been identified in one reference frame.
In this case, a temporal predictor for the side information pixel Y(p) is replaced by the co-located pixel of Y(p) in the upsampled hash frame, that is W ̃ p. In other words, when motion estimation is considered not to be trusted, the hash itself is assumed to convey more dependable information.
The average YUV PSNR is given by PSNR YUV = (4 × PSNR Y + PSNR U + PSNR V )/6. Figure 7 also evaluates the impact of the flexible scheme that enables the proposed OBME method to identify erroneous motion vectors and to replace the temporal predictor pixel with the decoded and interpolated hash.
However, some temporal predictors may stem from rather unreliable motion vectors.
The pixels in these best matching blocks act as temporal predictors for the co-located pixels in the predicted block.
Finally, the pixel values in the predicted WZ frame are calculated as the average of the candidate temporal predictors at every pixel position.
During the motion compensation process, the obtained predictors per pixel, whether being temporal predictors or taken from the upsampled hash, are combined to perform multi-hypothesis pixel-based prediction.
As a result, each pixel Y(p) in the side information frame has a number of associated temporal predictors r k, u n in the blocks R k, u n.
The co-located pixels in the estimated blocks R ̃ k = 0, m i - v k = 0 i, R ̃ k = 1, m i - v k = 1 i serve as potential temporal predictors for the current motion-compensated pixel position.
The resulting 29 candidate models were based on our hypotheses and can be divided into four spatiotemporal factor sets based on local predictors (assessed on the scale of the site), landscape predictors across different spatial scales (landscape), temporal predictors (season) and their combinations, and the null model (Table 1).
