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 coding using morphological pyramid decomposition.

L A Overturf1, M L Comer, E J Delp

  • 1Comput. Vision and Image Process. Lab., Purdue Univ., West Lafayette, IN.

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|January 1, 1995
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

Specular Highlight Removal For Image-Based Dietary Assessment.

... IEEE International Conference on Multimedia and Expo workshops. IEEE International Conference on Multimedia and Expo·2017
Same author

Image Segmentation for Image-Based Dietary Assessment: A Comparative Study.

ISSCS 2013 : International Symposium on Signals, Circuits and Systems : 11-12 July, 2013, Iasi, Romania : program. International Symposium on Signals, Circuits, and Systems (12th : 2013 : Iasi, Romania)·2017
Same author

New mobile methods for dietary assessment: review of image-assisted and image-based dietary assessment methods.

The Proceedings of the Nutrition Society·2016
Same author

Merging dietary assessment with the adolescent lifestyle.

Journal of human nutrition and dietetics : the official journal of the British Dietetic Association·2013
Same author

Digital correction of motion artefacts in microscopy image sequences collected from living animals using rigid and nonrigid registration.

Journal of microscopy·2011
Same author

Digital and optical moiré detection of flaws applied to holographic nondestructive testing.

Optics letters·2009
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
Same journal

BayeTopo: Bayesian-based Topology-guided Learning for Vascular Imaging Segmentation.

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

A novel algorithm uses mathematical morphology and block truncation coding for efficient pyramidal color image compression. This method achieves acceptable image quality at moderate data rates, with useful progressive transmission capabilities.

Area of Science:

  • Digital Image Processing
  • Computer Vision
  • Image Compression

Background:

  • Efficient color image compression is crucial for reducing storage and transmission bandwidth.
  • Pyramidal coding offers advantages in computational complexity and parallel implementation.
  • Existing methods may not balance compression ratio, image quality, and transmission features effectively.

Purpose of the Study:

  • To introduce a new algorithm for pyramidal coding of color images.
  • To achieve lossy color image compression using block truncation coding at pyramid levels.
  • To evaluate the algorithm's performance in terms of data rates and image quality.

Main Methods:

  • Utilized mathematical morphology for the core pyramidal coding structure.
  • Applied block truncation coding (BTC) at each pyramid level for data reduction.

Related Experiment Videos

  • Developed a lossy compression scheme targeting moderate data rates.

    • Main Results:

    • Demonstrated successful color image compression using the proposed pyramidal approach.
    • Achieved experimental results at data rates as low as 1.89 bits/pixel.
    • Highlighted the algorithm's ability to produce acceptable color image quality.

    Conclusions:

    • The pyramidal coding algorithm offers an attractive solution for color image compression.
    • The method's low computational complexity and parallel implementation facilitate practical use.
    • Progressive transmission capability enhances its utility in various applications.