Near-infrared multi-spectral imaging with Bayer-filter color cameras: a single-exposure approach for soot and temperature diagnostics
Why this work is in the frame
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Bibliographic record
Abstract
The color camera's application in combustion diagnostics is limited by the lack of absolute calibration methods, particularly in the near-infrared range. This study introduces a calibration approach for color cameras with Bayer filter arrays that extracts multi-wavelength spectral radiance from a single raw RGB image. By leveraging a matched multi-bandpass filter and the spectral sensitivity of the channels, the method compensates for spectral overlaps and eliminates the need for multiple exposures. Demonstrated on an ethylene-air flame with spectral emission and light extinction measurements at 550, 660, and 850 nm, the results are in agreement with prior studies, showcasing the potential of color cameras for near-infrared imaging in high-accuracy combustion diagnostics.
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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