MétaCan
Menu
Back to cohort
Record W2384554286

Application of Biorthogonal Wavelet Transform in Image Fusion

2006· article· en· W2384554286 on OpenAlexvenueno aff
Zhang Jing

Bibliographic record

VenueMicrocomputer applications · 2006
Typearticle
Languageen
FieldEngineering
TopicAdvanced Image Fusion Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceImage fusionArtificial intelligenceWaveletComputer visionFusionImage (mathematics)Wavelet transformBiorthogonal waveletOperator (biology)Image qualityFusion rulesBiorthogonal systemMultiresolution analysisPattern recognition (psychology)Discrete wavelet transform
DOInot available

Abstract

fetched live from OpenAlex

Principle and methods about multi-sensor image fusion technology have been studied. Based on the characteristics of multi-resolution and direction of wavelet analyzing, a novel layered image fusion method on the wavelet multi-scale analyzing has established, and the new fusion ruler and fusion operator also have been provided. Experimental results show that this methodis more effective than the others. After treated on this method, the image quality has been apparently improved.

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.

How this classification was reachedexpand

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: Methods · Consensus signal: Methods
Teacher disagreement score0.340
Threshold uncertainty score0.566

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 head0.002
GPT teacher head0.202
Teacher spread0.200 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreMethods

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".

Quick stats

Citations0
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueMicrocomputer applicationsSame topicAdvanced Image Fusion TechniquesFrench-language works237,207