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Related Concept Videos

Visual System01:26

Visual System

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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.
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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.
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Anatomy of the Eyeball01:20

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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...
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Gestalt Principles of Perception01:21

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Gestalt principles provide a framework for understanding how humans perceive objects as unified wholes within their context. These principles are essential in explaining the cognitive processes that make sense of complex visual stimuli by organizing them into coherent groups. One fundamental principle is proximity, which posits that objects located close to each other are perceived as a collective group. For instance, when dots are positioned near one another, the visual system interprets them...
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Color Vision01:24

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Color perception begins in the retina, the light-sensitive layer at the back of the eye. Two main theories explain how colors are seen: the trichromatic theory and the opponent-process theory. The trichromatic theory, proposed by Thomas Young in 1802 and extended by Hermann von Helmholtz in 1852, suggests that color vision is based on three types of cone receptors in the retina. These cones are sensitive to different but overlapping ranges of wavelengths corresponding to red, blue, and green.
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At the molecular level, visual signals trigger transformations in photopigment molecules, resulting in changes in the photoreceptor cell's membrane potential. The photon's energy level is denoted by its wavelength, with each specific wavelength of visible light associated with a distinct color. The spectral range of visible light, classified as electromagnetic radiation, spans from 380 to 720 nm. Electromagnetic radiation wavelengths exceeding 720 nm fall under the infrared category,...
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Visualizing Visual Adaptation
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Visual Orientation Selectivity Based Structure Description.

Jinjian Wu, Weisi Lin, Guangming Shi

    IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
    |July 29, 2015
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a novel structure descriptor inspired by the human visual system. This descriptor effectively captures spatial correlations for improved image processing and quality assessment.

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    Area of Science:

    • Computer Vision
    • Neuroscience
    • Image Processing

    Background:

    • Existing structure descriptors primarily focus on luminance contrast, neglecting spatial correlations.
    • The human visual system excels at extracting structure information for scene perception.

    Purpose of the Study:

    • To introduce a novel, rotation-invariant structure descriptor inspired by the orientation selectivity mechanism of the primary visual cortex.
    • To enhance image processing by effectively representing spatial correlations in structure.

    Main Methods:

    • Computed pixel correlations based on preferred orientation similarities, mimicking excitatory/inhibitory cell arrangements.
    • Developed an orientation selectivity-based pattern by binarizing correlations.
    • Integrated gradient magnitude with the orientation selectivity-based pattern to create a rotation-invariant descriptor.

    Main Results:

    • The proposed descriptor demonstrated robustness to disturbances and effectively represented structure degradation.
    • Applied successfully in texture classification and reduced-reference image quality assessment, proving its generality.

    Conclusions:

    • The orientation selectivity-based structure descriptor offers a robust and effective method for representing spatial structure information.
    • This approach advances image processing by incorporating insights from visual neuroscience.