A Dimmed Display Image Enhancement Technique for Energy Conservation
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
Lowering the brightness of digital displays as a means to reduce power consumption and extend battery life is a widely adopted strategy. However, this course of action inevitably results in decreased image contrast and a negative influence on the overall image quality. In this paper, we propose a method to enhance the visual quality of dimmed displays while keeping the overall brightness and power consumption unchanged. First, we amplify the contrast and brightness of each frame utilizing the human contrast sensitivity function (CSF). Subsequently, we introduce a technique for reducing brightness based on the concept of the just noticeable difference (JND), ensuring that the average brightness remains at the level of the initially dimmed frame, thus aligning with the targeted power consumption. Our subjective evaluation indicated that the integration of our CSF based enhancement method and our proposed JND based brightness reduction method yield superior visual quality, while preserving the mean brightness of the original image.
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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 | 0.001 |
| 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