On multirate optimality of JPEG2000 code stream
Bibliographic record
Abstract
Arguably, the most important and defining feature of the JPEG2000 image compression standard is its R-D optimized code stream of multiple progressive layers. This code stream is an interleaving of many scalable code streams of different sample blocks. In this paper, we reexamine the R-D optimality of JPEG2000 scalable code streams under an expected multirate distortion measure (EMRD), which is defined to be the average distortion weighted by a probability distribution of operational rates in a given range, rather than for one or few fixed rates. We prove that the JPEG2000 code stream constructed by embedded block coding of optimal truncation is almost optimal in the EMRD sense for uniform rate distribution function, even if the individual scalable code streams have nonconvex operational R-D curves. We also develop algorithms to optimize the JPEG2000 code stream for exponential and Laplacian rate distribution functions while maintaining compatibility with the JPEG2000 standard. Both of our analytical and experimental results lend strong support to JPEG2000 as a near-optimal scalable image codec in a fairly general setting.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".