The 2-directional wavelet transform: Theory and implementation
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
The 2-directional wavelet transform is an image representation which separates the spectrum of an image into a lowpass subband, a horizontal highpass subband and a vertical high-pass subband. Each of the decomposed highpass subbands, corresponding to pairwise trapezoidal regions of the spectrum of an original image, is critically sampled to a rectangular shaped coefficient image in the spatial domain. This paper illustrates how an innovative method can be generated by the creative combination of filter banks, integer resampling, and frequency shifting. The proposed 2-directional wavelet transform achieves critical sampling and perfect reconstruction properties. The new transform is an extension of the traditional wavelet transform, and is also the fundamental stage of a new method called the nonredundant contourlet transform (NRCT) developed in a companion paper. Experimental results are presented to demonstrate the potential of the 2- directional wavelet transform.
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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