Low-Cost Lifting Architecture and Lossless Implementation of Daubechies-8 Wavelets
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Bibliographic record
Abstract
This paper presents three lifting structures of Daubechies-8 (also known as D8) wavelet transform using efficient factorization of the polyphase matrix. All new filter coefficients are optimally mapped with integers resulting in low cost hardware implementation. We first derive the polyphase matrices using a factorization algorithm, which forms the basis of multiple lifting structures of D8. A theoretical framework is then derived and proven experimentally to eliminate the scaling stage of the algorithm that incurs computation error in conventional integer-based wavelets. This elimination of the scaling stage makes the proposed architecture lossless. Also due to the optimum integer mapping, the 8-bit implementation of our schemes produces very similar results than that of the classical double-precision D8 filter. Finally, we compare our results with other existing lifting wavelets to demonstrate the advantage in terms of lower cost, losslessness and improved performance.
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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 | 0.000 |
| Open science | 0.000 | 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