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

Color image enhancement via chromaticity diffusion.

B Tang1, G Sapiro, V Caselles

  • 1Dept. of Electr. and Comput. Eng., Minnesota Univ., Minneapolis, MN 55455, USA.

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|February 6, 2008
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

Dissociation of UPR signaling and ER ultrastructure during 4-PBA therapy in shunt-driven pulmonary hypertension.

American journal of hypertension·2026
Same author

Endoscopic endonasal versus transcranial approaches for trigeminal schwannomas: choosing the optimal surgical corridor based on tumour traits.

Rhinology·2025
Same author

Utilising Digital Ocular Imaging for Paediatric Retinal Haemorrhages.

Irish medical journal·2025
Same author

Motivations for Self-Harm in Young People and Their Correlates: A Systematic Review.

Clinical child and family psychology review·2025
Same author

[Quercetin ameliorates diabetic kidney injury in rats by inhibiting the HMGB1/RAGE/NF-κB signaling pathway].

Nan fang yi ke da xue xue bao = Journal of Southern Medical University·2024
Same author

Preparation and application of high thermal conductivity phase change microcapsules with fluorescence characteristics based on a ZnWO<sub>4</sub> shell.

Nanoscale·2024
Same journal

Mask-guided Asymmetric Contrastive and Semantic Alignment for Unsupervised Person Re-Identification.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

Hyperbolic Cycle Alignment for Infrared-Visible Image Fusion.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

Learning Gaze Synthesizer via 3D-eye Controlled Diffusion and Cross-domain Feature Alignment.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

Underlying Semantic Diffusion for Effective and Efficient In-Context Learning.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

DiffRES: Unleashing Text-to-Image Diffusion Models for Generative Referring Expression Segmentation without Information Leakage.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

Location Matters: Frequency-Spatial Dual Space Adaptation for Cross-Domain Few-Shot Segmentation.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
See all related articles

This study introduces a new color image denoising method by separating color data into chromaticity and brightness. Processing these components with partial differential equations effectively reduces noise while preserving image quality.

Area of Science:

  • Computer Vision
  • Image Processing
  • Computational Mathematics

Background:

  • Color image denoising remains a challenge, with existing methods often struggling to preserve fine details and color fidelity.
  • Vectorial data processing, particularly for directional information like chromaticity, requires specialized regularization techniques.

Purpose of the Study:

  • To propose a novel algorithm for color image denoising.
  • To leverage partial differential equations (PDEs) and diffusion flows for processing chromaticity and brightness components separately.
  • To adapt harmonic map theory for robust chromaticity regularization.

Main Methods:

  • Representing each color pixel as an n-dimensional vector, with direction for chromaticity and magnitude for brightness.
  • Applying coupled diffusion equations, derived from harmonic map theory, to regularize chromaticity while maintaining unit norm.

Related Experiment Videos

  • Utilizing scalar median filters or anisotropic diffusion for brightness component enhancement.
  • Implementing both isotropic and anisotropic diffusion for chromaticity processing.

    • Main Results:

    • The proposed method effectively denoises color images by treating chromaticity and brightness distinctly.
    • Demonstration of the underlying theory through various examples.
    • Comparison with existing literature highlights the advantages of the novel approach.

    Conclusions:

    • The novel approach offers a robust framework for color image denoising by separating and processing chromaticity and brightness components.
    • The adaptation of harmonic map theory provides a principled way to regularize vectorial chromaticity data.
    • The method shows promise for enhancing image quality in various applications.