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

Robust, object-based high-resolution image reconstruction from low-resolution video.

P E Eren1, M I Sezan, A M Tekalp

  • 1Dept. of Electr. Eng., Rochester Univ., NY.

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|January 1, 1997
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

Projection method formulations of Hopfield-type associative memory neural networks.

Applied optics·2010
Same author

A new motion-compensated reduced-order model Kalman filter for space-varying restoration of progressive and interlaced video.

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

End-to-end color printer calibration by total least squares regression.

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

Tracking visible boundary of objects using occlusion adaptive motion snake.

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

Motion segmentation by multistage affine classification.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·1997
Same author

Superresolution video reconstruction with arbitrary sampling lattices and nonzero aperture time.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·1997
Same journal

Style-Aware Contrastive Test-Time Adaptation: A Dual-Cache Model for Robust Vision-Language Alignment.

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

Semantic Frame Interpolation.

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

Physics-Guided Cross-Modal Decoupling with Test-Time Adaptation for Hyperspectral Image Restoration.

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

Change-Prior-Guided Unsupervised Change Detection of Heterogeneous Remote Sensing Images.

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

AgonicDreamer: Enhancing Multi-View Consistency in Text-to-3D Generation via Rectified Score Distillation.

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

BiCM-Prompt: Bidirectional Cross-Modal Prompt Tuning for Class-Incremental Learning on Multisource Remote Sensing Images.

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

This study introduces an object-based method for high-resolution image reconstruction from video. It enhances image quality by using validity and segmentation maps to manage motion estimation errors.

Area of Science:

  • Computer Vision
  • Image Processing
  • Signal Processing

Background:

  • High-resolution image reconstruction from video is crucial for various applications.
  • Existing methods can be sensitive to motion estimation errors, degrading reconstruction quality.
  • Object-based processing offers potential for improved accuracy but requires robust motion modeling.

Purpose of the Study:

  • To develop a robust, object-based approach for high-resolution image reconstruction from video.
  • To enhance image quality by mitigating the impact of motion estimation inaccuracies.
  • To introduce novel validity and segmentation maps for improved reconstruction.

Main Methods:

  • Utilized the projections onto convex sets (POCS) framework for image reconstruction.

Related Experiment Videos

  • Developed a validity map to exclude projections with inaccurate motion information.
  • Implemented a segmentation map for object-based processing with refined motion models.

    • Main Results:

    • Experimental results demonstrate significant improvements in reconstructed image quality.
    • The validity map effectively handles motion estimation errors, ensuring robust reconstruction.
    • The segmentation map enables more accurate object-based motion modeling, further enhancing quality.

    Conclusions:

    • The proposed object-based approach significantly improves high-resolution image reconstruction from video.
    • Validity and segmentation maps are effective tools for robust and high-quality reconstruction.
    • The method offers a promising solution for applications requiring accurate video-based image enhancement.