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 Concept Videos

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...
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...
Naturalistic Observations02:30

Naturalistic Observations

If you want to understand how behavior occurs, one of the best ways to gain information is to simply observe the behavior in its natural context. However, people might change their behavior in unexpected ways if they know they are being observed. How do researchers obtain accurate information when people tend to hide their natural behavior? As an example, imagine that your professor asks everyone in your class to raise their hand if they always wash their hands after using the restroom. Chances...
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.
Difference from Background: Limit of Detection01:05

Difference from Background: Limit of Detection

The limit of detection (LOD) is the smallest amount of analyte that can be distinguished from the background noise. The LOD value corresponds to the concentration at which the analyte signal is three times larger than the standard deviation of the blank signal. Below this value, the analyte signal cannot be differentiated from the background noise. It is calculated by dividing the calibration slope by 3 times the standard deviation of the blank signals.
The LOD indicates the presence or absence...

You might also read

Related Articles

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

Sort by
Same author

Deepfake perpetrator conversation for adults with sexual abuse-related posttraumatic stress disorder: intervention development and multiple baseline study protocol.

European journal of psychotraumatology·2026
Same author

Virtual rescripting after loss using deepfake technology in prolonged grief treatment: a study protocol for a multiple baseline design.

European journal of psychotraumatology·2026
Same author

Interactive Learning of Intrinsic and Extrinsic Properties for All-Day Semantic Segmentation.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2023
Same author

Geometric Back-Propagation in Morphological Neural Networks.

IEEE transactions on pattern analysis and machine intelligence·2023
Same author

Corrigendum: Initial development of perpetrator confrontation using deepfake technology in victims with sexual violence-related PTSD and moral injury.

Frontiers in psychiatry·2023
Same author

Initial development of perpetrator confrontation using deepfake technology in victims with sexual violence-related PTSD and moral injury.

Frontiers in psychiatry·2022
Same journal

HardFlow: Hard-Constrained Sampling for Flow-Matching Models Via Trajectory Optimization.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Industrial Brain: Self-Evolving Neuro-Symbolic Autonomy with Causal Resilience for Cyber-Physical Systems.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Adaptive Hardness-Driven Dictionary Distillation for Incomplete Streaming View Clustering.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Mixture of Global and Local Experts with Diffusion Transformer for Controllable Face Generation.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Task-KV: Task-aware KV Cache Optimization via Semantic Differentiation of Attention Heads.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Achieving Text-based Person Retrieval with Any Granularity.

IEEE transactions on pattern analysis and machine intelligence·2026
See all related articles

Related Experiment Video

Updated: Jun 13, 2026

Visualizing Visual Adaptation
04:43

Visualizing Visual Adaptation

Published on: April 24, 2017

Color constancy using natural image statistics and scene semantics.

Arjan Gijsenij1, Theo Gevers

  • 1Faculty of Science, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands.

IEEE Transactions on Pattern Analysis and Machine Intelligence
|April 28, 2010
PubMed
Summary
This summary is machine-generated.

Selecting the best color constancy algorithm for any image is challenging. This study uses natural image statistics and Weibull parameterization to identify image characteristics, enabling selection of the optimal color constancy method for improved performance.

More Related Videos

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters
07:05

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters

Published on: June 18, 2021

Qualitative Identification of Carboxylic Acids, Boronic Acids, and Amines Using Cruciform Fluorophores
09:46

Qualitative Identification of Carboxylic Acids, Boronic Acids, and Amines Using Cruciform Fluorophores

Published on: August 19, 2013

Related Experiment Videos

Last Updated: Jun 13, 2026

Visualizing Visual Adaptation
04:43

Visualizing Visual Adaptation

Published on: April 24, 2017

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters
07:05

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters

Published on: June 18, 2021

Qualitative Identification of Carboxylic Acids, Boronic Acids, and Amines Using Cruciform Fluorophores
09:46

Qualitative Identification of Carboxylic Acids, Boronic Acids, and Amines Using Cruciform Fluorophores

Published on: August 19, 2013

Area of Science:

  • Computer Vision
  • Image Processing
  • Computational Photography

Background:

  • Existing color constancy algorithms rely on specific image assumptions, limiting their universal applicability.
  • No single algorithm performs optimally across all image types due to diverse spatial and spectral characteristics.

Purpose of the Study:

  • To develop a method for selecting the best color constancy algorithm for a specific image.
  • To leverage natural image statistics for adaptive algorithm selection and combination.

Main Methods:

  • Utilized natural image statistics to identify key image characteristics.
  • Employed Weibull parameterization to capture image attributes like grain size and contrast.
  • Used a Gaussian Mixture Model (MoG) classifier to correlate Weibull parameters with image attributes (edges, texture, SNR).

Main Results:

  • Demonstrated a relationship between Weibull parameterization and image attributes sensitive to color constancy methods.
  • Achieved significant performance improvements over state-of-the-art single algorithms, with up to a 20% median angular error reduction.
  • Showcased that specific algorithms may suffice for certain scene categories, potentially replacing complex classifiers.

Conclusions:

  • Natural image statistics, characterized by Weibull parameters, can effectively guide the selection of color constancy algorithms.
  • The proposed method offers a robust approach to enhance color constancy performance across a wide range of images.
  • Adaptive algorithm selection based on image characteristics provides a substantial advantage over universal, single-algorithm approaches.