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

The structure of images.

J J Koenderink

    Biological Cybernetics
    |January 1, 1984
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a unique mathematical method to analyze image structure across different resolutions. It reveals that images are composed of nested structures, like light and dark blobs, each visible at specific resolutions.

    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

    Method of stabilizing the retinal image.

    Applied optics·2010
    Same author

    Spatiotemporal contrast detection threshold surface is bimodal.

    Optics letters·2009
    Same author

    Do reference surfaces influence exocentric pointing?

    Acta psychologica·2008
    Same author

    Optical properties (bidirectional reflectance distribution function) of shot fabric.

    Applied optics·2008
    Same author

    Surface roughness from highlight structure.

    Applied optics·2008
    Same author

    Optical properties (bidirectional reflection distribution functions) of velvet.

    Applied optics·2008

    Area of Science:

    • Computer Vision
    • Image Processing
    • Perception Science

    Background:

    • Image details are scale-dependent, crucial for visual perception.
    • Existing mathematical theories lack a framework for multi-resolution image analysis.

    Purpose of the Study:

    • To develop a mathematically formulated theory for image structure at varying resolutions.
    • To uniquely embed images into a resolution-parameterized family of derived images.

    Main Methods:

    • Applied a constraint to prevent spurious detail generation during resolution reduction.
    • Utilized the diffusion equation to govern the structure of derived image families.
    • Characterized image structure as a nested set of blobs appearing at specific resolutions.

    Related Experiment Videos

    Main Results:

    • Demonstrated a unique method to derive image families based on resolution.
    • Showed that decreasing resolution erodes image articulation by eliminating extrema (blobs).
    • Established that each image blob has a specific resolution range for its manifestation.

    Conclusions:

    • Any image can be uniquely represented as nested structures (blobs) with resolution-specific visibility.
    • The derived image family structure allows for calculating required sampling densities for multi-scale analysis.
    • This framework integrates with existing theories of visual system processing.