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

A maximum likelihood approach for image registration using control point and intensity.

Winston Li1, Henry Leung

  • 1Department of Electrical and Computer Engineering, University of Calgary, Calgary, AB T2N 1N4, Canada. winston_li66@yahoo.com

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|August 26, 2004
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

Hyperspectral Anomaly Detection via Hybrid Convolutional and Transformer-Based U-Net With Error Attention Mechanism.

IEEE transactions on neural networks and learning systems·2025
Same author

SmartTex - A DIY Textile-Based Multi-Modal Sensing System for Non-Invasive Health Monitoring Applications.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same author

The Light at the End of the Tunnel: Promise and Peril in the Resident to Attending Transition.

Academic psychiatry : the journal of the American Association of Directors of Psychiatric Residency Training and the Association for Academic Psychiatry·2025
Same author

Integrating Learners Into Telemedicine Encounters.

Academic medicine : journal of the Association of American Medical Colleges·2025
Same author

Dual-Modal Approach for Ship Detection: Fusing Synthetic Aperture Radar and Optical Satellite Imagery.

Sensors (Basel, Switzerland)·2025
Same author

Realizing the Potential of Commercial E-Textiles for Wearable Glucose Biosensing Application.

ACS materials Au·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 an exact maximum likelihood (EML) method for image registration, combining control points (CP) and intensity data. The new EML approach improves image alignment accuracy compared to traditional methods.

Area of Science:

  • Computer Vision
  • Image Processing
  • Remote Sensing

Background:

  • Image registration is crucial for applications like remote sensing and medical imaging.
  • Existing methods often rely solely on control points (CP) or intensity data.

Purpose of the Study:

  • To propose a novel image registration method combining both CP and intensity features.
  • To enhance the accuracy of image alignment using an exact maximum likelihood (EML) approach.

Main Methods:

  • Developed an exact maximum likelihood (EML) registration method.
  • The EML method estimates registration parameters, including affine transformation and CP coordinates.
  • Derived Cramer-Rao bounds (CRB) for performance evaluation.

Main Results:

Related Experiment Videos

  • The proposed EML method integrates both CP and intensity for improved registration.
  • Performance evaluation using CRB demonstrates the effectiveness of the EML technique.
  • Explicit CRB formulas were derived for both EML and conventional algorithms.

Conclusions:

  • The EML registration method offers a robust approach for accurate image alignment.
  • Combining CP and intensity data enhances registration performance.
  • The derived CRBs provide a benchmark for evaluating image registration algorithms.