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Record W2167216303 · doi:10.1109/tcsvt.2004.825573

Efficient Channel Protection for JPEG2000 Bitstream

2004· article· en· W2167216303 on OpenAlexaff
Víctor Sánchez, Mrinal Mandal

Bibliographic record

VenueIEEE Transactions on Circuits and Systems for Video Technology · 2004
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Data Compression Techniques
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsComputer scienceBitstreamConcatenation (mathematics)Channel (broadcasting)Robustness (evolution)Redundancy (engineering)Bit error rateConvolutional codeAlgorithmBit rateReal-time computingDecoding methodsComputer networkMathematicsArithmetic

Abstract

fetched live from OpenAlex

An adaptive unequal channel protection technique is proposed for JPEG2000 compressed images exploiting the hierarchical structure of the coded bit stream. The proposed technique takes into account the effect of the channel errors in different packets of the bit stream in order to optimally protect the coded data according to the channel conditions. The robustness of the proposed technique is evaluated over a Rayleigh-fading channel with a concatenation of a cyclic redundancy check code and a rate-compatible convolutional code. Comparisons are made with the cases of equal channel protection and unequal channel protection across the layers. Simulation results show a significant improvement in subjective and objective quality of the received images.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.028
GPT teacher head0.264
Teacher spread0.236 · 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 designSimulation or modeling
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

Citations32
Published2004
Admission routes1
Has abstractyes

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