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Record W1968072296 · doi:10.1364/josaa.17.001744

Theory of spatiochromatic image encoding and feature extraction

2000· article· en· W1968072296 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

VenueJournal of the Optical Society of America A · 2000
Typearticle
Languageen
FieldComputer Science
TopicImage Retrieval and Classification Techniques
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsFourier transformHueChromatic scaleArtificial intelligenceSpatial frequencyComputer scienceColor spaceOpticsComputer visionPattern recognition (psychology)MathematicsAlgorithmPhysicsImage (mathematics)Mathematical analysis

Abstract

fetched live from OpenAlex

We consider how to interpret, filter, and cross-correlate complex-value color (hue and saturation) images by using a single discrete Fourier transform: the spatiochromatic discrete Fourier transform. The model defines new types of spatiochromatic oriented sinusoidal gratings, termed rainbow gratings, which encode the variation of color over space. We demonstrate how color-opponent detectors observed within the vertebrate visual system can be easily defined by linear filters within this representation. This model also allows us to filter and detect both spatial and chromatic patterns in images by using a single cross-correlation procedure. In doing so, we explore a new form of the Cauchy-Schwartz inequality applied to complex-valued scalar products. Results demonstrate the power of this form of spatiochromatic matched filtering in detecting signals embedded in such a significant amount of noise that they are not visible to the unaided human eye.

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: Methods · Consensus signal: none
Teacher disagreement score0.565
Threshold uncertainty score0.144

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 head0.009
GPT teacher head0.254
Teacher spread0.245 · 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