Space-frequency motion model for subband/wavelet video coding
Bibliographic record
Abstract
Wavelet-transform lossy coding achieves state-of-the-art performance for still images. For motion-compensated interframes, however, block-transform coding is preferred due to its ability to intracode poorly predicted blocks. Space-frequency half-pixel block matching is a new approach that enables hybrid block-motion-compensated wavelet-coded interframes to efficiently code blocks with low temporal correlation of high-frequency details. Architectural compatibility is maintained and little additional complexity is required to achieve superior performance. Simulation results with both fixed-size block matching and hierarchical-variable-sized block matching indicate that a block size-constrained adaptive choice of interpolation filter improves the PSNR by 0.75 dB for hybrid wavelet interframe coding (versus +0.25 dB for H.263) at multimedia quality bit rates. For H.263, bit rate reduction can approach 30% at higher rates. The method is perceptually successful where a block-translational motion model fails, efficiently reducing falsely introduced detail.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".