Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Parallel Processing

Parallel Processing

The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...

Visual System

Visual System

Light enters the eye through the cornea, a transparent, dome-shaped surface covering the surface of the eyeball that helps to direct and focus incoming light. This light is then channeled toward the pupil, an adjustable opening whose size is controlled by the iris. The iris, a pigmented muscle, regulates the amount of light entering the eye by contracting or dilating the pupil, thereby ensuring optimal light levels for clear vision.
Once through the pupil, the light passes through the lens, a...

Vision

Vision

Vision is the result of light being detected and transduced into neural signals by the retina of the eye. This information is then further analyzed and interpreted by the brain. First, light enters the front of the eye and is focused by the cornea and lens onto the retina—a thin sheet of neural tissue lining the back of the eye. Because of refraction through the convex lens of the eye, images are projected onto the retina upside-down and reversed.

You might also read

Related Articles

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

Sort by

Same author

Simultaneous co-cultivation of the thermoacidophilic methanotroph, <i>Methylacidiphilum</i> sp. RTK17.1, and the microalga, <i>Galdieria</i> sp. RTK37.1, for single cell protein production.

Engineering microbiology·2026

Same author

Oxygen competition induces chlorosis in thermoacidophilic methanotroph-microalgae cocultures.

Biotechnology for biofuels and bioproducts·2026

Same author

DSOF: A Rapid Method to Determine the Abundance of Microalgae and Methanotrophic Bacteria in Coculture Using a Combination of Differential Sedimentation, Optical Density, and Fluorescence.

Bioengineering (Basel, Switzerland)·2025

Same author

Roadmap of Anaphylaxis Registries Across the World.

Clinical and experimental allergy : journal of the British Society for Allergy and Clinical Immunology·2025

Same author

Frequencies and predictors of subcutaneous and intraosseous injection with 4 epinephrine autoinjector devices.

Annals of allergy, asthma & immunology : official publication of the American College of Allergy, Asthma, & Immunology·2024

Same author

Pilot-Scale Production of Hemicellulose Ethers from Softwood Hemicelluloses Obtained from Compression Screw Pressate of a Thermo-Mechanical Pulping Plant.

Polymers·2023

Search research articles

Related Experiment Videos

Hyperconnections and hierarchical representations for grayscale and multiband image processing.

Benjamin Perret¹, Sébastien Lefevre, Christophe Collet

¹Image Science, Computer Science and Remote Sensing Laboratory (LSIIT, Unités Mixtes de Recherche 7005) University of Strasbourg–National Center for Scientific Research, Pôle API, Strasbourg, France. bperret@unistra.fr

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society

|July 12, 2011

Summary

This summary is machine-generated.

This study introduces a new axiomatic for hyperconnections (h-connections) in image processing, enabling consistent image decompositions and filter design. The research presents a tree-based framework for analyzing these decompositions, enhancing image segmentation and filtering tasks.

Related Experiment Videos

Area of Science:

Computer Vision
Image Processing
Mathematical Morphology

Background:

Connections define pixel grouping based on spatial and gray-level properties.
Hyperconnections (h-connections) offer a promising new theory for image analysis.
Existing theories lack consistent decomposition methods for filter design.

Purpose of the Study:

To propose a new axiomatic for h-connections ensuring consistent image decomposition.
To develop a general tree-based framework for representing image decompositions into h-connections.
To apply and validate the framework for image segmentation, filtering, and binarization.

Main Methods:

Development of a novel axiomatic system for hyperconnections.
Construction of a generalized connected component tree for h-connection decompositions.
Application of a fuzzy h-connection to classical image processing tasks.

Main Results:

The proposed axiomatic ensures consistent decompositions for h-connected filters.
The tree framework provides an efficient method for attribute filtering and detection.
Experiments demonstrate robustness to noise and suitability for selective filtering.

Conclusions:

The new axiomatic and tree framework advance the theory of hyperconnections in image processing.
The approach offers an efficient and intuitive method for designing selective image filters.
The framework is effective for various applications including segmentation and binarization.