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Record W1985228139 · doi:10.1109/apccas.2006.342137

New Encoding of 8ո DCT to make H.264 Lossless

2006· article· en· W1985228139 on OpenAlexaff
Khan A. Wahid, Vassil S. Dimitrov, G.A. Jullien

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicVideo Coding and Compression Technologies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsDiscrete cosine transformQuantization (signal processing)Computer scienceLossless compressionEncoding (memory)EncoderAlgorithmTranscendental functionField-programmable gate arrayTransform codingArithmeticTheoretical computer scienceComputer hardwareData compressionMathematicsArtificial intelligenceImage (mathematics)

Abstract

fetched live from OpenAlex

This paper presents a fast algorithm to compute the 8times8 discrete cosine transform (DCT), using a new error-free encoding which partially overcomes the quantization error of digital implementation due to finite-precision effect. The proposed encoding scheme, named as algebraic integer quantization (AIQ), is achieved by obtaining the exact representation of the transcendental functions. The proposed AIQ-based 8times8 DCT can be used as an alternative transform for H.264 encoders, which results in a simple, parallel, and multiplication-free architecture, and also minimizes the complexity and the hardware cost of the quantizer/dequantizer. The authors propose an initial FPGA implementation where the system can run at 100 MHz, and satisfies all real time constraints for digital multimedia applications

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.016
GPT teacher head0.242
Teacher spread0.226 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

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

Citations14
Published2006
Admission routes1
Has abstractyes

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