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In order to obtain progressive images, missing pixels have to be reconstructed using linear filters according to the spatial correlations, the temporal correlations, and both the spatial and temporal correlations in interlaced video sequences.
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Since the original LST maps can be cloud-contaminated or have missing pixels due to other problems, we reconstructed all maps to complete maps before using them for our study [35].
Same feature maps are plotted in the bottom rows, where each of them has several missing pixels.
It is clearly to see that the feature maps in facial recognition have much more missing pixels than the ones in the emotion recognition.
Furthermore, after the inpainting, the reconstructed pixels have the values less than one, i.e., the reconstructed pixels have higher reliability than that of the missing pixels but lower reliability than that of the original pixels.
The colors of the missing pixels thereby are predicted simultaneously, allowing prediction in cases where the entire neighborhoods of pixels have to be predicted.
Bottom row: feature maps with missing pixels.
In this case, the missing pixels are interpolated by the weighted average of neighboring pixels.
The technology compares every frame in a video to find and replace missing pixels.
A little lion statue, however, looked great except for some missing pixels around the head.
Fig. 5 The pixel grid with question marks denote missing pixels not properly determined by the Shift-Add fusion technique.
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