Optimizing the Lagrange multiplier in perceptually-friendly high efficiency video coding for mobile applications
Why this work is in the frame
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Bibliographic record
Abstract
In mobile applications, the amount of memory and bandwidth is restricted. Efficient compression of video is essential to provide better quality streaming on a mobile device. High efficiency video coding (HEVC) standard provide substantial bitrate savings compared with the previous standards. The compression efficiency of HEVC has been improved by integration of a perceptual video quality metric inside the encoder. In the rate distortion optimization process, PSNR-HVS has been used to measure distortion for the coding unit mode selection. In this paper, we find the optimal Lagrange multiplier based on the quantization parameter. Experimental results for various test sequences show the compression efficiency of the perceptual HEVC will be improved by finding the optimal Lagrange multiplier.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.004 | 0.001 |
| 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 it