Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

A perceptually lossless, model-based, texture compression technique.

P Campisi1, D Hatzinakos, A Neri

  • 1Dipartimento di Ingegneria Elettronica, Universitá degli Studi di Roma Tre, I-00146 Roma, Italy. campisi@ele.uniroma3.it

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|February 12, 2008
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

A network meta-analysis of randomized clinical trials in lenalidomide-exposed or -refractory multiple myeloma patients.

ESMO open·2025
Same author

Outcomes and prognostic indicators in daratumumab-refractory multiple myeloma: a multicenter real-world study of elotuzumab, pomalidomide, and dexamethasone in 247 patients.

ESMO open·2025
Same author

Reggio Emilia (Northern Italy) Interdisciplinary Uveitis Clinic: What We Have Learned in the Last 20 Years.

Ocular immunology and inflammation·2024
Same author

Preliminary assessment of persistent organic pollutants (POPs) in tissues of Risso's dolphin (Grampus griseus) specimens stranded along the Italian coasts.

Marine pollution bulletin·2022
Same author

Transcriptomic landscape of TIMP3 oncosuppressor activity in thyroid carcinoma.

Cancer cell international·2022
Same author

Corrigendum to "Cast iron street furniture: A historical review" [Endeavour 44 (3) (2020) 100721].

Endeavour·2021
Same journal

Hyperbolic Cycle Alignment for Infrared-Visible Image Fusion.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

Learning Gaze Synthesizer via 3D-eye Controlled Diffusion and Cross-domain Feature Alignment.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

Underlying Semantic Diffusion for Effective and Efficient In-Context Learning.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

DiffRES: Unleashing Text-to-Image Diffusion Models for Generative Referring Expression Segmentation without Information Leakage.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

Location Matters: Frequency-Spatial Dual Space Adaptation for Cross-Domain Few-Shot Segmentation.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

BayeTopo: Bayesian-based Topology-guided Learning for Vascular Imaging Segmentation.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
See all related articles

This study introduces a novel texture coding method for image compression. It achieves perceptually lossless compression by synthesizing textures, outperforming existing techniques.

Area of Science:

  • Computer Vision
  • Image Processing
  • Signal Processing

Background:

  • Natural images and sequences often contain complex textural structures.
  • Efficiently coding these textures is essential for image compression.

Purpose of the Study:

  • To present a novel, perceptually lossless, synthesis-by-analysis texture coding method.
  • To improve upon existing texture compression techniques.

Main Methods:

  • A model-based approach using a binary excitation signal and a parsimonious reconstruction filter representation.
  • Compression of estimated model parameters via a lossless strategy.
  • Utilizing a fast binary wavelet transformation tailored for binary images.

Main Results:

Related Experiment Videos

  • The method synthesizes textures perceptually indistinguishable from the original.
  • Achieved very good perceptual results.
  • Demonstrated superior performance compared to existing texture coding methods.

Conclusions:

  • The proposed synthesis-by-analysis method offers an effective solution for perceptually lossless texture compression.
  • The tailored binary wavelet transformation enhances the efficiency of the lossless compression stage.
  • This approach advances the state-of-the-art in image and texture coding.