Viewing angle enhancement for two- and three-dimensional holographic displays with random superresolution phase masks
Bibliographic record
Abstract
Holographic displays employing binary phase modulation have been demonstrated to be attractive on the grounds of efficiency and miniaturization, and they offer a plausible approach to two-dimensional (2D) and three-dimensional (3D) image projection and display. A novel algorithm--one-step phase retrieval--and corresponding hardware architecture have recently been proposed, providing the performance required for real-time holographic display. However, since viewing angle varies inversely with pixel size, very small display pixels are required to achieve a wide field of view. This is particularly problematic for 3D displays, as the requirement for a large display with small pixels has hitherto necessitated an unachievably large electrical bandwidth. We present a novel approach, utilizing fixed random pixelated quaternary phase masks of greater resolution than the displayed hologram, to dramatically increase the viewing angle for 2D and 3D holographic displays without incurring a bandwidth penalty or significantly degrading image quality. Furthermore, an algorithm is presented to generate holograms accounting for the presence of such a phase mask, so that only one mask is required.
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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 | 0.001 |
| 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".