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Perceptual Constancy01:12

Perceptual Constancy

Perceptual constancy is the ability to recognize that objects remain consistent and unchanged even when their appearance varies due to changes in sensory input. There are four main types of perceptual constancy: size constancy, shape constancy, color constancy, and brightness constancy.
Size constancy is the recognition that an object remains the same size, even when its image on the retina changes. For instance, a bus is perceived to be large enough to carry people, even if it looks tiny from...
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,...
Color Vision01:24

Color Vision

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.
Gestalt Principles of Perception01:21

Gestalt Principles of Perception

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...
Depth Perception and Spatial Vision01:15

Depth Perception and Spatial Vision

Depth perception is the ability to perceive objects three-dimensionally. It relies on two types of cues: binocular and monocular. Binocular cues depend on the combination of images from both eyes and how the eyes work together. Since the eyes are in slightly different positions, each eye captures a slightly different image. This disparity between images, known as binocular disparity, helps the brain interpret depth. When the brain compares these images, it determines the distance to an object.

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Related Experiment Video

Updated: Jul 7, 2026

Visualizing Visual Adaptation
04:43

Visualizing Visual Adaptation

Published on: April 24, 2017

Locally adaptive perceptual image coding.

I Höntsch1, L J Karam

  • 1Telecommunications Research Center, Department of Electrical Engineering, Arizona State University, Tempe, AZ 85287-7206, USA. hontsch@asu.edu

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|February 12, 2008
PubMed
Summary
This summary is machine-generated.

This study introduces a novel perceptual image coder that adapts quantization to human visual masking properties. This locally adaptive approach improves image compression quality and bit rate without extra data, outperforming non-adaptive methods.

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Area of Science:

  • Computer Vision
  • Image Processing
  • Signal Processing

Background:

  • Existing image compression methods prioritize mathematical distortion metrics over perceptual quality.
  • Non-perceptual metrics fail to correlate with perceived quality at lower bit rates and may not preserve crucial visual details.

Purpose of the Study:

  • To develop a perceptual image coder that enhances compression performance by focusing on visually relevant components.
  • To improve image and video compression efficiency and perceived quality, especially at lower bit rates.

Main Methods:

  • A locally adaptive perceptual quantization scheme is proposed, exploiting human visual masking properties.
  • Visual masking thresholds are derived adaptively within subband decomposition.
  • Quantizer reconstruction levels are adjusted based on local masking in each subband transform coefficient.

Main Results:

  • The locally adaptive algorithm demonstrates superior performance compared to non-locally adaptive methods.
  • The method achieves better quality and bit rate without requiring additional side information.
  • Perceptually redundant information is effectively removed, leading to a low-entropy image representation.

Conclusions:

  • The proposed locally adaptive perceptual quantization scheme offers significant advantages for image compression.
  • The approach is well-suited for perceptually lossless image compression due to its efficiency and lack of side information.
  • Exploiting human visual masking properties leads to more effective and perceptually relevant image compression.