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

Analysis and enhancements to piecewise linear comparametric image registration.

Frank M Candocia1

  • 1Department of Electrical and Computer Engineering, Florida International University, Miami, FL 33174, USA. frank.candocia@fiu.edu

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|February 11, 2005
PubMed
Summary

This study enhances piecewise linear comparametric image registration with slope constraints and knot selection. These improvements reduce errors and handle registration gaps effectively.

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

Simultaneous homographic and comparametric alignment of multiple exposure-adjusted pictures of the same scene.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2008
Same author

Jointly registering images in domain and range by piecewise linear comparametric analysis.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2008
Same author

A semiparametric model for accurate camera response function modeling and exposure estimation from comparametric data.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2005
See all related articles

Area of Science:

  • Medical Imaging
  • Computer Vision
  • Image Processing

Background:

  • Piecewise linear comparametric image registration is a crucial technique.
  • Previous methods had limitations in error reduction and handling complex cases.

Purpose of the Study:

  • To introduce enhancements to piecewise linear comparametric image registration.
  • To improve accuracy and robustness of the registration process.

Main Methods:

  • Incorporated slope constraints into the comparametric modeling.
  • Developed a knot location selection method based on reference image pixel distribution.

Main Results:

  • The proposed enhancements reduce registration error and sensitivity to segment count.

Related Experiment Videos

  • The method successfully addresses cases with gaps in the comparagram.
  • Demonstrated effectiveness on real-world medical images.

    • Conclusions:

    • The enhanced comparametric modeling offers improved performance for image registration.
    • This approach provides a more robust solution for challenging registration scenarios.