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

Multiresolution Gauss-Markov random field models for texture segmentation.

S Krishnamachari1, R Chellappa

  • 1Dept. of Image Process., COMSAT Lab., Clarksburg, MD.

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|January 1, 1997
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

Formalin dab, the effective way of treating haemorrhagic radiation proctitis: a randomized trial from a tertiary care hospital in South India.

Colorectal disease : the official journal of the Association of Coloproctology of Great Britain and Ireland·2012
Same author

Classification of partial 2-d shapes using fourier descriptors.

IEEE transactions on pattern analysis and machine intelligence·2011
Same author

Estimation of object motion parameters from noisy images.

IEEE transactions on pattern analysis and machine intelligence·2011
Same author

Fourier coding of image boundaries.

IEEE transactions on pattern analysis and machine intelligence·2011
Same author

Activity modeling using event probability sequences.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2008
Same author

Separability-based multiscale basis selection and feature extraction for signal and image classification.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2008
Same journal

Style-Aware Contrastive Test-Time Adaptation: A Dual-Cache Model for Robust Vision-Language Alignment.

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

Semantic Frame Interpolation.

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

Physics-Guided Cross-Modal Decoupling with Test-Time Adaptation for Hyperspectral Image Restoration.

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

Change-Prior-Guided Unsupervised Change Detection of Heterogeneous Remote Sensing Images.

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

AgonicDreamer: Enhancing Multi-View Consistency in Text-to-3D Generation via Rectified Score Distillation.

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

BiCM-Prompt: Bidirectional Cross-Modal Prompt Tuning for Class-Incremental Learning on Multisource Remote Sensing Images.

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

This study introduces multiresolution models for Gauss-Markov random fields (GMRFs) to improve texture segmentation. The novel approach enhances accuracy and reduces computational cost compared to single-resolution methods.

Area of Science:

  • Computer Vision
  • Image Processing
  • Statistical Modeling

Background:

  • Texture segmentation is crucial for image analysis.
  • Gauss-Markov random fields (GMRFs) are effective for modeling textures.
  • Existing methods often lack computational efficiency and accuracy.

Purpose of the Study:

  • To develop and evaluate multiresolution models for GMRFs.
  • To improve texture segmentation accuracy and reduce computational load.
  • To approximate non-Markov random fields at coarser resolutions using Markov fields.

Main Methods:

  • Subsampling fine-resolution GMRF sample fields to create coarser resolutions.
  • Estimating GMRF parameters at coarser resolutions using Kullback-Leibler distance minimization and local conditional distribution invariance.

Related Experiment Videos

  • Applying multiresolution texture segmentation using iterated conditional mode (ICM) minimization.

    • Main Results:

    • The multiresolution GMRF model effectively approximates Markov fields at coarser resolutions.
    • Parameter estimation techniques were developed for GMRF at different resolutions.
    • Experiments demonstrated improved segmentation accuracy and reduced computation on synthetic, Brodatz, and satellite images.

    Conclusions:

    • Multiresolution GMRF models offer a computationally efficient and accurate approach to texture segmentation.
    • The proposed method outperforms single-resolution algorithms in both accuracy and speed.
    • The technique is robust across various image types.