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Related Concept Videos

Visual System01:26

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...
Vision01:24

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.
Anatomy of the Eyeball01:20

Anatomy of the Eyeball

The eye is a spherical, hollow structure composed of three tissue layers. The outer layer — the fibrous tunic, comprises the sclera — a white structure — and the cornea, which is transparent. The sclera encompasses some of the ocular surface, most of which is not visible. However, the 'white of the eye' is distinctively visible in humans compared to other species. The cornea, a clear covering at the front of the eye, enables light penetration. The eye's middle layer, the vascular tunic,...

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Related Experiment Videos

Infrared and Visible Image Fusion Using Bimodal Neuron and Dynamic Receptive Field Mechanisms.

Shaobing Gao, Minjie Tan, Shun Lv

    IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
    |May 6, 2026
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a novel infrared and visible image fusion (IVIF) framework inspired by snake sensory systems. The new method enhances scene interpretation by effectively integrating infrared and visible light information.

    Related Experiment Videos

    Area of Science:

    • Computer Vision
    • Biologically-Inspired Computing
    • Image Processing

    Background:

    • Infrared and visible image fusion (IVIF) is crucial for enhanced scene interpretation.
    • Existing methods often struggle to fully leverage the complementary information from different spectra.
    • Biological systems, like those in snakes, offer advanced models for multimodal sensory integration.

    Purpose of the Study:

    • To develop a novel IVIF framework inspired by the bimodal sensory system of snakes.
    • To integrate nonlinear cross-modal interactions and dynamic receptive fields into a deep neural network (DNN).
    • To improve the accuracy and detail preservation in fused infrared and visible images.

    Main Methods:

    • A novel IVIF framework was designed, incorporating mathematical formalizations of snake bimodal neuron interactions and receptive fields.
    • A deep neural network (DNN) was employed, optimized using object detection region-guided and frequency-dependent fusion losses.
    • The model was trained and evaluated on multiple datasets for image fusion, object detection, and semantic segmentation.

    Main Results:

    • The proposed model successfully emulates the infrared-visible information integration observed in snake bimodal neurons.
    • The nonlinear bimodal neurons significantly improved the capture of edge information and high-frequency details.
    • The fused images demonstrated superior performance in object detection and semantic segmentation tasks under various lighting conditions.

    Conclusions:

    • The biologically-inspired DNN framework offers a powerful approach for infrared and visible image fusion.
    • The model achieves state-of-the-art performance, outperforming traditional methods and matching other advanced DNNs.
    • This research highlights the potential of leveraging neuro-ethological principles for advanced image processing applications.