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Record W1968080121 · doi:10.1002/col.21768

Perceptual uniformity in digital image representation and display

2013· article· en· W1968080121 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

VenueColor Research & Application · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicColor Science and Applications
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsRGB color modelComputer graphics (images)Computer visionComputer scienceLuminanceArtificial intelligenceDigital imageGraphicsPerceptionPixelCoding (social sciences)GamutImage processingImage (mathematics)MathematicsPsychology

Abstract

fetched live from OpenAlex

Digital image representation is perceptually uniform if a small perturbation of a component value—such as the digital code value used to represent red, green, blue, or luminance—produces a change in light output at a display that is approximately equally perceptible across the range of that value. Most digital image coding systems—including sRGB (used in desktop graphics), BT.709 (used in high‐definition television, HD), Adobe RGB (1998) (used in graphics arts), and DCI P3 RGB (used in digital cinema)—represent colour component (pixel) values in a perceptually uniform manner. However, this behavior is not well documented and is often shrouded in confusion. This article surveys perceptual uniformity in digital imaging and attempts to clarify some widely misunderstood aspects of image coding. © 2013 Wiley Periodicals, Inc. Col Res Appl, 39, 6–15, 2014

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.546
Threshold uncertainty score0.783

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.029
GPT teacher head0.371
Teacher spread0.342 · 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