Flexible Spectrally-Scanning Snapshot Multispectral Imaging On Dual-Tap Coded-Exposure-Pixel CMOS Image Sensors
Bibliographic record
Abstract
We present a method of spectrally-scanning snapshot multispectral imaging (MSI) that employs a dual-tap coded-exposure-pixel (CEP) CMOS image sensor. A frame exposure time is divided into N subexposures. During each subexposure, an arbitrarily programmable exposure code is sent to each pixel to control the integration of the photogenerated charge into one of the two taps. We employ the data-memory pixel (DMP) architecture for the CEP, which achieves the smallest pixel size of all CEP sensors. Five unique-wavelength LEDs are sequentially turned on, synchronously with five unique 2x2-pixel code tiles, and submitted to the sensor over five subexposures. The sorted photogenerated charges are read out, and five images at the five wavelengths are subsequently extracted by demultiplexing. The number of wavelengths is flexible and can be easily extended using a larger pixel tile. As a result, spectra for a scene are captured at 5 wavelengths in the visible light and NIR spectrum in a single frame, at 30 frames per second, without using a color filter array.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".