Analog Encoding Voltage—A Key to Ultra-Wide Dynamic Range and Low Power CMOS Image Sensor
Why this work is in the frame
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Bibliographic record
Abstract
Usually Wide Dynamic Range (WDR) sensors that autonomously adjust their integration time to fit intra-scene illumination levels use a separate digital memory unit. This memory contains the data needed for the dynamic range. Motivated by the demands for low power and chip area reduction, we propose a different implementation of the aforementioned WDR algorithm by replacing the external digital memory with an analog in-pixel memory. This memory holds the effective integration time represented by analog encoding voltage (AEV). In addition, we present a “ranging” scheme of configuring the pixel integration time in which the effective integration time is configured at the first half of the frame. This enables a substantial simplification of the pixel control during the rest of the frame and thus allows for a significantly more remarkable DR extension. Furthermore, we present the implementation of “ranging” and AEV concepts on two different designs, which are targeted to reach five and eight decades of DR, respectively. We describe in detail the operation of both systems and provide the post-layout simulation results for the second solution. The simulations show that the second design reaches DR up to 170 dBs. We also provide a comparative analysis in terms of the number of operations per pixel required by our solution and by other widespread WDR algorithms. Based on the calculated results, we conclude that the proposed two designs, using “ranging” and AEV concepts, are attractive, since they obtain a wide dynamic range at high operation speed and low power consumption.
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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