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 Experiment Videos

Spectral sharpening: sensor transformations for improved color constancy

G D Finlayson1, M S Drew, B V Funt

  • 1School of Computing Science, Simon Fraser University, Vancouver, B.C., Canada.

Journal of the Optical Society of America. A, Optics, Image Science, and Vision
|May 1, 1994
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Color constancy at a pixel.

Journal of the Optical Society of America. A, Optics, image science, and vision·2001
Same author

Diagonal versus affine transformations for color correction.

Journal of the Optical Society of America. A, Optics, image science, and vision·2000
Same journal

Multi-module collaborative optimization-driven fast speckle correlation imaging in variable environments.

Journal of the Optical Society of America. A, Optics, image science, and vision·2026
Same journal

Secrecy performance analysis of NOMA-UWOC systems over a vertically stratified WGG oceanic turbulence channel.

Journal of the Optical Society of America. A, Optics, image science, and vision·2026
Same journal

Backscattering of plane waves in a composite system containing a rough surface and anisotropic scatterers.

Journal of the Optical Society of America. A, Optics, image science, and vision·2026
Same journal

Aspherical surface construction methods based on extended Jacobi polynomials.

Journal of the Optical Society of America. A, Optics, image science, and vision·2026
Same journal

OCT sidelobe suppression method based on dual-path phase sinusoidal modulation and minimum value fusion.

Journal of the Optical Society of America. A, Optics, image science, and vision·2026
Same journal

Optical design concepts using wavelength-selective diffractive optics to enable miniaturized multimodal endoscopic imaging across separated spectral ranges.

Journal of the Optical Society of America. A, Optics, image science, and vision·2026
See all related articles

Spectral sharpening transforms improve color constancy algorithms by concentrating sensor sensitivities. These methods enhance how visual systems process color under varying illumination, aligning with human perception.

Area of Science:

  • Computer Vision
  • Color Science
  • Computational Neuroscience

Background:

  • Color constancy algorithms often rely on independent adjustment of sensor response channels.
  • Diagonal-matrix transforms (DMT) are commonly used for this adjustment, seen in models like Retinex and von Kries adaptation.

Purpose of the Study:

  • To develop sensor transformations, termed spectral sharpening, to enhance color constancy algorithm performance.
  • To investigate methods for creating new sensor sensitivity functions that improve channel independence.

Main Methods:

  • Sensor-based sharpening: Creating new sensors as linear combinations of existing ones to concentrate spectral sensitivity.
  • Data-based sharpening: Optimizing new sensors using response vectors from surfaces under different illuminants.

Related Experiment Videos

  • Perfect sharpening: Demonstrating a unique optimal transform under specific illumination and reflectance models.

    • Main Results:

    • All three spectral sharpening techniques produced similar, effective results.
    • Using sharpened cone sensitivities with a DMT significantly improved modeling of illumination changes.
    • Diagonal-matrix transforms performed nearly as well as more complex non-diagonal transforms.

    Conclusions:

    • Spectral sharpening is an effective method for improving color constancy algorithms.
    • The developed techniques align with psychophysical evidence of spectral sharpening in the human visual system.
    • The findings suggest that optimized sensor sensitivities are key to robust color constancy.