Improvement of JPEG2000 Using Curved Wavelet Transform
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Bibliographic record
Abstract
The wavelet transform in JPEG2000 is performed using one-dimensional (1D) filtering in the vertical and horizontal directions. This conventional wavelet transform is not effective to represent edges and lines in images. In this paper we present a curved wavelet transform that improves the performance of JPEG200. The curved wavelet transform is performed using 1D filtering along curves that are usually parallel to edges and lines in images. The pixels along these curves can be well represented by a small number of wavelet coefficients. A simple algorithm is proposed in this paper to determine the curves according to image content. Experimental results show that the curved wavelet transform can significantly improve the compression efficiency of JPEG2000, especially for images that contain sharp edges and lines. The coding gain can be up to 1.6 dB in the terms of PSNR.
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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