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Record W1973185243 · doi:10.1889/1.2785211

3.2: High Dynamic Range Projection Systems

2007· article· en· W1973185243 on OpenAlex

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

VenueSID Symposium Digest of Technical Papers · 2007
Typearticle
Languageen
FieldEngineering
TopicAdvanced Optical Imaging Technologies
Canadian institutionsUniversity of British ColumbiaDolby (Canada)
Fundersnot available
KeywordsLuminanceHigh dynamic rangeComputer scienceDynamic rangeProjection (relational algebra)Image qualityImplementationComputer visionModulation (music)Computer graphics (images)Liquid-crystal displaySpatial light modulatorArtificial intelligenceImage (mathematics)OpticsPhysics

Abstract

fetched live from OpenAlex

Abstract Digital cinema and home theatre applications need to compete with analog film in terms of image quality. The single most important performance specification of a projection system, and the largest gap in the competition between digital and analog projectors, is the relatively low dynamic range of luminance of current digital projectors. In this paper we introduce a novel digital system capable of displaying images with a high enough dynamic range to rival analog film. The projection system described is based on a serial combination of light modulating devices, such as two liquid crystal micro‐display panels within a projection light engine. One of the modulation steps can be of lower spatial resolution and contrast. This increases the optical efficiency of the system and avoids optical artifacts. We describe several hardware implementations of this approach as well as the required image processing. Finally, we present an evaluation of the designs in terms of performance, image quality and cost.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.661
Threshold uncertainty score0.876

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 head0.005
GPT teacher head0.225
Teacher spread0.220 · 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