Robust subband image coding for wireless transmission
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Emerging wireless networks and multimedia developments are making compressed image transmission over noisy channels more widespread. However, most image compression algorithms have been developed without considering error robustness. While they are usually efficient in terms of compression, they are very sensitive to channel errors. In this paper, we propose a robust image compression algorithm based on lattice vector quantization where the dimension of the vector quantizer is matched to each processed subband in a wavelet based coder. The method also employs vector indexation in order to reduce or even eliminate the entropy coding stage, which is usually responsible for the poor performance of image coders in noisy environments. The proposed method yields compression performance levels similar to those achieved by the current JPEG-2000 standard verification model, but performs substantially better in terms of error resilience.
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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 | 0.000 | 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 it