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Record W2123880679 · doi:10.1109/ccece.2005.1557049

Reconfigurable, fully scalable integer wavelet transform unit for JPEG2000

2006· article· en· W2123880679 on OpenAlexaff
Rami Zewail, Philip Marshall, S. Kozicki, Nanjiao Ying, D.G. Elliott, N.G. Durdle

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Data Compression Techniques
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsComputer scienceDiscrete wavelet transformLifting schemeWavelet transformJPEG 2000WaveletSecond-generation wavelet transformParallel computingImage compressionScalabilityStationary wavelet transformComputational scienceAlgorithmComputer hardwareArtificial intelligenceImage processingImage (mathematics)

Abstract

fetched live from OpenAlex

The new still compression image standard, JPEG2000, has emerged with a number of significant features that would allow it to be used efficiently over a wide variety of images. The scalability of this new standard allows trading off between compression rate and quality of image. Due to the multi-resolution nature of wavelet transforms, they have been adopted by the JPEG2000 standard as the transform of choice. In this work, we present an implementation for a re configurable fully scalable integer wavelet transform (IWT) unit that satisfies the specifications of the JPEG2000 standard. The implementation is based on the lifting scheme, which is the most computation efficient implementation of the discrete wavelet transform. Integer wavelet transforms, also known as reversible DWT, have recently received special interest due to a number of significant properties in terms of computational efficiency and storage requirements. The lifting scheme-based integer wavelet transform (IWT) unit was implemented in field programmable gate arrays (FPGAs), namely the Xilinx Vertix II family. The design is scalable in order to allow a trade off between rate and distortion. A maximum clock frequency of 112 MHz, with throughput of over 400 pixels/s, was achieved by employing techniques such as parallel operation of independent units and pipelining. A speed up of over 61 times has been achieved versus a Matlab compiled C code implementation on a Pentium IV 1.8 GHZ processor

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: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.430
Threshold uncertainty score0.632

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 communication0.0000.001
Open science0.0010.000
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 head0.016
GPT teacher head0.261
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

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 designNot applicable
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

Citations1
Published2006
Admission routes1
Has abstractyes

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