Block Tree Partitioning for Wavelet Based Color Image Compression
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
This paper presents a new algorithm for wavelet based image compression by exploiting zero tree concept in the wavelet decomposed image. The algorithm has a big edge over previously developed wavelet based image compression algorithms in that it utilizes inter and intra band correlation simultaneously, something that previous algorithms failed to exploit. Besides the improvement in coding efficiency, the algorithm also uses significantly lower memory for computation and coding thereby reducing the complexity of the algorithm. The striking feature of the algorithm is pass independent coding that makes it suitable for application to error protection schemes and makes it less vulnerable to data loss due to noisy communication channel. The algorithm codes all the color bands independently thus enabling differential coding for the color information. The paper starts with the discussion of the concept underlying the algorithm and then sees the algorithm in a broader light. Comparisons have been made to SPIHT, the well known zero tree coder for wavelet based image compression in terms of coding efficiency, memory requirements and error resiliency.
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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