Multiplication-free architecture for Daubechies wavelet transforms using algebraic integers
Bibliographic record
Abstract
The 2-Dimensional Wavelet Transform has been proven to be a highly effective tool for image analysis and used in JPEG2000 standard. There are many publications which demonstrate that using wavelet transform in time and space, combined with a multiresolution approach, leads to an efficient and effective method of compression. In particular, the four and six coefficient Daubechies filters have excellent spatial and spectral locality, properties which make them useful in image compression. In this paper, we propose a multiplication-free and parallel VLSI architecture for Daubechies wavelets where the computations are free from round-off errors until the final reconstruction step. In our algorithm, error-free calculations are achieved by the use of Algebraic Integer encoding of the wavelet coefficients. Compared to other DWT algorithms such as: embedded zero-tree, recursive or semi-recursive and conventional fixed-point binary architecture, our technique has lower hardware cost, lower computational power and optimized data-bus utilization.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 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".