A hybrid approach of wavelet packet and directional decomposition for image compression
Bibliographic record
Abstract
In this paper, a novel image compression technique, the combination of wavelet packet transform and directional decomposition, is proposed. Wavelet packet transform is an increasingly remarkable approach which outperforms the standard wavelet transform in image coding. It can be employed to exploit the image redundancy efficiently and therefore obtain a high compression ratio. Directional filtering coding technique, as one of the "second generation image coding techniques", first introduced the concept of directional decomposition. By placing emphasis on edge detection to preserve edge information to exploit the fact that the human visual system is more sensitive to image edge features, it is generally capable to obtain a relatively high compression ratio. The approach proposed in this paper decomposed an image into a low frequency component and a number of high frequency components, with the edges on each high frequency component at its own directions. By a combination process of Cartesian coordinate rotation transform, interpolation, wavelet packet transform, and a coding algorithm, the image is reconstructed at an improved visual quality at the same bitrate compared to the common wavelet pyramid algorithm.
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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".