A variable quantization technique for image compression using integer Tchebichef transform
Why this work is in the frame
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Bibliographic record
Abstract
In the field of image and data compression there is always a need for novel transform coding techniques promising improved reconstruction and reduced computational complexity. The usage of integer adaptation of the popular discrete cosine transform (DCT) with fixed quantization is prevalent in the field of video compression due to its ease of computation and acceptable performance. However, there exist other polynomial-based orthogonal transforms like discrete Tchebichef transform (DTT), which possess valuable properties like energy compaction, but are potentially unexploited in comparison. The influence of specific features, such as the structure and content, of the image on the quality of reconstructed image after decompression is undeniable. This paper aims to harness this aspect and introduces a technique to adapt the quantization performed during compression according to the characteristics of the image block without any additional computational or transmission overhead. The image compression performance of integer DTT and integer DCT, using both variable and fixed quantization, are evaluated and compared.
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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 | 0.003 |
| 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