Efficient direct 2D architecture for lifted biorthogonal DWT
Bibliographic record
Abstract
The paper presents a new algorithm for 2D nonseparable lifted biorthogonal wavelet transform. The algorithm is derived by factoring complementary pairs of wavelet transform filters written as (L/spl times/M) tap 2D filters. The results are efficient architectures for real time signal processing, which do not require transpose memory for 2D processing of data. The proposed architecture exploits the in-place implementation inherited from the algorithm and can take advantage of both vertical and horizontal parallelism in the direct implementation. Processing in the architecture is scheduled carefully by pipelining the lifted steps, which allows two or four times faster processing than the direct implementation. The architecture therefore allows lowering of the clock frequency by two/four. The proposed architecture operates at high speed, consumes low power and has reduced computational complexity as compared to already published filter and lifting-based biorthogonal wavelet architectures.
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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 | 0.000 |
| 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 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".