Laser speckle reduction utilized by lens vibration for laser projection applications
Bibliographic record
Abstract
Abstract In this paper, a compact speckle reduction method utilizing vibrating lenses for laser beam scanning is proposed and demonstrated. The maximum speckle reduction efficiency was found to be 75.6% and 81.25% for a 532 nm diode-pumped solid-state (DPSS) laser and a 520 nm laser diode (LD), respectively. The minimum speckle contrast ratio observed using our method was 0.11 for the DPSS laser and 0.06 for the LD. The proposed method can provide speckle reduction with minimal power requirements, a low implementation cost, and no bending for the optical path of the laser beam. Additionally, this method is promising to withstand high-power lasers for use in high lumen laser projectors by optimizing the lens parameters. The demonstrated technique has a small form factor while simultaneously demonstrating a high degree of speckle reduction, which shows potential for speckle reduction in mini- and pico- laser projector applications.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".