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

Analyzing image structure by multidimensional frequency modulation.

Marios S Pattichis1, Alan C Bovik

  • 1Department of Electrical Engineering and Computer Engineering, University of New Mexico, Albuquerque, NM 87131, USA. pattichis@ece.unm.edu

IEEE Transactions on Pattern Analysis and Machine Intelligence
|March 16, 2007
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

Joint Quality Assessment and Example-Guided Tone Mapping by Disentangling Picture Appearance From Content.

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

Quality Prediction of Embedded and Overlaid Text in User-Generated Visual Content.

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

SAMScore: A Content Structural Similarity Metric for Image Translation Evaluation.

IEEE transactions on artificial intelligence·2026
Same author

HoloQA: Full Reference Video Quality Assessor of Rendered Human Avatars in Virtual Reality.

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

Constructing Per-Shot Bitrate Ladders Using Visual Information Fidelity.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2025
Same author

No-Reference Image Quality Assessment Leveraging GenAI Images.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2025
Same journal

Relation DETR+: Exploring Explicit Position Relation Prior for Dense Prediction.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

RBF++: Quantifying and Optimizing Reasoning Boundaries across Measurable and Unmeasurable Capabilities for Chain-of-Thought Reasoning.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

CAFE: Cross-View Adaptive Fusion and Cluster Center Enhancement for Robust Multi-View Clustering.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

DIVER: Reinforced Diffusion Breaks Imitation Bottlenecks in End-to-End Autonomous Driving.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Ethics-Aware Safe Reinforcement Learning for Rare-Event Risk Control in Interactive Urban Driving.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Learning Shape Anchors for Holistic Indoor Scene Understanding.

IEEE transactions on pattern analysis and machine intelligence·2026
See all related articles

We introduce a mathematical framework to analyze frequency modulations in digital images using the instantaneous frequency gradient tensor (IFGT). This method enhances image pattern analysis for textures and fingerprints.

Area of Science:

  • Digital Image Processing
  • Mathematical Imaging
  • Signal Processing

Background:

  • Multidimensional frequency modulations are crucial for analyzing complex image textures.
  • Existing methods may not fully capture the intricate dynamics of nonstationary image data.
  • Understanding local regularity in textures is key to advanced image analysis.

Purpose of the Study:

  • To develop a novel mathematical framework for quantifying multidimensional frequency modulations in digital images.
  • To introduce the instantaneous frequency gradient tensor (IFGT) for advanced image analysis.
  • To provide new tools for analyzing image textures with local regularity.

Main Methods:

  • Defined the instantaneous frequency vector (IF) as the phase gradient.

Related Experiment Videos

  • Introduced the instantaneous frequency gradient tensor (IFGT) as derivatives of the IF vector.
  • Derived frequency modulation bounds via IFGT eigendecomposition.
  • Formulated ordinary differential equations (ODEs) for image flowlines using the IFGT.
  • Studied ODE diagonalization on the IFGT eigenvector coordinate system.

    • Main Results:

    • Established a quantitative framework for multidimensional frequency modulations.
    • Demonstrated the utility of IFGT for image pattern analysis.
    • Identified IFGT eigenvectors as coordinates for separable transform computation.
    • Successfully applied methods to analyze textured and fingerprint images.

    Conclusions:

    • The IFGT provides a powerful tool for understanding and quantifying frequency modulations in digital images.
    • The derived methods offer new approaches for analyzing nonstationary image textures with local regularity.
    • This framework has potential applications in various fields requiring detailed image texture analysis.