An embedded wavelet image coder with parallel encoding and sequential decoding of bit-planes
Bibliographic record
Abstract
Wavelet based coders are widely used in image and video compression. Many popular embedded wavelet coders are based on a data structure known as zerotree. However, there exists a category of embedded wavelet coders that are fast and efficient even without zerotrees. These coders are based on three key concepts: (1) wavelet coefficient reordering; (2) bit-plane partition; and (3) encoding of bit-planes with efficient run-length coding. In this paper, we propose a bit-plane encoder that can be used in these non-zerotree algorithms. Instead of encoding the bit-planes sequentially, the bit-plane encoding process can be completed in one pass when multiple bit-plane encoders are used simultaneously. This bit-plane encoder is inherently suitable for parallel processing architecture. The decoding process is treated sequentially since each bit-plane stream can only be synchronized upon the correct decoding of higher bit-planes. To the best of our knowledge, this paper is the first to realize parallelization through encoding multiple bit-planes simultaneously.
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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".