Multiplexing of luminance and chrominance in NTSC compatible extended definition systems based on subsampling
Bibliographic record
Abstract
Methods are presented for luminance-chrominance multiplexing in an NTSC (National Television System Committee) compatible extended-definition transmission scheme based on subsampling. A one-dimensional multiplexing scheme has been illustrated with a 4:1 interlaced sampling structure based on HD-MAC. This one-dimensional multiplexing scheme can also be used with the Triscan 6:1 interlaced sampling structure in a straightforward way. A two-dimensional multiplexing scheme has also been illustrated, this time using a modified Triscan sampling structure. These techniques allow methods similar to those proposed in Europe for HDTV (high-definition television) broadcasting to be used with the NTSC system. Then, all the techniques which have been developed for compatible HD-MAC to improve the quality of the compatible picture and to improve motion rendition in the HD picture can be brought to bear on this scheme. These include preprocessing and postprocessing to reduce flicker in the compatible image and motion-compensated processing for improved interpolation and moving areas in the HD picture.>
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".