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

Model-based vector quantization with application to remotely sensed image data.

M Manohar1, J C Tilton

  • 1Dept. of Comput. Sci, Bowie State Univ., MD 20715, USA. manohar@cs.bowiestate.edu

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

Evaluation of drug release efficiency and antibacterial property of a pH-responsive dextran-based silver nanocomposite hydrogel.

International journal of biological macromolecules·2024
Same author

Axial compression tests on CFRP strengthened CFS plain angle short columns.

Scientific reports·2024
Same author

Prediction of DDoS attacks in agriculture 4.0 with the help of prairie dog optimization algorithm with IDSNet.

Scientific reports·2023
Same author

Novel electrochemical biosensor key significance of smart intelligence (IoMT & IoHT) of COVID-19 virus control management.

Process biochemistry (Barking, London, England)·2022
Same author

A Paradigm Shift in the Development of Anti-Candida Drugs.

Current topics in medicinal chemistry·2019
Same author

A comparative study evaluating the role of adductor canal block catheter versus intraarticular analgesic infusion on knee pain and range of motion in the immediate postoperative period: a prospective multicenter trial.

Musculoskeletal surgery·2019
Same journal

Mask-guided Asymmetric Contrastive and Semantic Alignment for Unsupervised Person Re-Identification.

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

Model-based vector quantization (MVQ) offers codebookless image compression, simplifying the process by eliminating intensive codebook generation and maintenance. This method uses a mathematical model and human visual system to regenerate codebooks during decoding, proving effective for remotely sensed imagery.

Area of Science:

  • Digital Image Processing
  • Data Compression
  • Computer Vision

Background:

  • Conventional vector quantization (VQ) requires computationally intensive pre-generated codebooks.
  • Codebook generation and maintenance present significant challenges in VQ systems.
  • Existing VQ methods often lack flexibility and efficiency in practical applications.

Purpose of the Study:

  • Introduce Model-based Vector Quantization (MVQ) as a novel, codebookless VQ variant.
  • Address the computational and maintenance burdens associated with traditional VQ codebooks.
  • Evaluate the performance of MVQ for compressing remotely sensed image data.

Main Methods:

  • MVQ utilizes a mathematical model for mean-removed errors and a human visual system model.
  • Parameterized codebooks are generated on-the-fly using an error model parameter (lambda).

Related Experiment Videos

  • The parameter lambda is transmitted as side information for codebook regeneration during decoding.

    • Main Results:

    • MVQ demonstrates competitive compression performance compared to other VQ techniques and JPEG/DCT.
    • The codebookless nature of MVQ significantly reduces computational complexity and simplifies system maintenance.
    • MVQ shows promise as a component in progressive image compression systems for archival and distribution.

    Conclusions:

    • MVQ offers a practical and efficient alternative to traditional VQ by eliminating codebook dependency.
    • The method is particularly suitable for applications involving remotely sensed imagery and large-scale archival.
    • MVQ's ability to regenerate codebooks enhances its utility in progressive image compression frameworks.