Lossless and reversible colour space transformation for Bayer colour filter array images
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
We present two variants of a colour space transformation algorithm to encode Bayer colour filter array images that are based on integer coefficients; as a result, the algorithms are fully lossless and reversible in nature. These transformation algorithms are derived using an optimisation model that reduces the spectral redundancy of Bayer colour components, which results in lower prediction error variance and inter‐colour correlation. These methods, known as optimum reversible colour space transform (ORCT‐1 and ORCT‐2), improve the lossless bitrate of low complexity prediction model without using high complexity interpolation and inter‐colour prediction scheme. Extensive experimentation is performed using five sets of test images for different lossless compression algorithms: JPEG‐LS, JPEG‐2000 and JPEG‐XR. Experimental results show that, in all cases, the proposed schemes perform competitively with other methods with lower computational complexity, which makes them suitable for low‐cost imaging applications.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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