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Record W4318148714 · doi:10.1117/12.2649281

Modeling and experiment on point spread function of refractive and metasurface microlens arrays used in 3D integral imaging light field displays

2023· article· en· W4318148714 on OpenAlex
Mahdi Safari, Sédick Rabia, Parsa Omidi, Simon Thibault, Herman M. K. Wong

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Optical Imaging Technologies
Canadian institutionsUniversité LavalHuawei Technologies (Canada)
Fundersnot available
KeywordsMicrolensIntegral imagingPoint spread functionLight fieldImage qualityOpticsFlexibility (engineering)Quality (philosophy)Computer scienceField (mathematics)Focal pointPoint (geometry)Focal lengthFunction (biology)Computer visionImage (mathematics)Artificial intelligenceLens (geology)Cardinal pointPhysicsMathematics

Abstract

fetched live from OpenAlex

Three-dimensional light field displays are not yet widely adopted due to the bulky form-factor and limited image quality caused by optical aberrations of microlens arrays (MLAs). Conventional optimization techniques cannot approach the maximal displayed image quality as they rely on intermediary metrics such as focal spot size. In order to optimize for the full-color wide field-of-view image quality, the point spread function of the MLA should be modeled to provide more flexibility. We developed a modeling approach for both refractive and metasurface MLAs and assessed the accuracy by judicious comparisons between the numerical simulations and experimental characterization.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.453
Threshold uncertainty score0.466

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.250
Teacher spread0.238 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Quick stats

Citations1
Published2023
Admission routes1
Has abstractyes

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