ML Anthology

USSR: A Unified Framework for Simultaneous Smoothing, Segmentation, and Registration of Multiple Images

Nicholas A. Lord, Jeffrey Ho, Baba C. Vemuri
ICCV 2007 pp. 1-6
doi:10.1109/ICCV.2007.4408969 /iccv/2007/lord2007iccv-ussr/

Abstract

Image smoothing, segmentation and registration are three key processing steps in many computer vision applications. In this paper, we present a novel framework for achieving all three seemingly disparate goals simultaneously across multiple images in a unified framework via a single variational principle. The proposed method ensures that the estimated registration is unbiased and all compositions of registration maps are compatible. The solution to the variational problem is achieved efficiently by solving a coupled system of partial differential equations over the common domain on which the registration maps are defined. The effectiveness of the proposed framework is demonstrated on sets of real images.

ICCV Semantic Scholar

Cite

Text

Lord et al. "USSR: A Unified Framework for Simultaneous Smoothing, Segmentation, and Registration of Multiple Images." IEEE/CVF International Conference on Computer Vision, 2007. doi:10.1109/ICCV.2007.4408969

Markdown

[Lord et al. "USSR: A Unified Framework for Simultaneous Smoothing, Segmentation, and Registration of Multiple Images." IEEE/CVF International Conference on Computer Vision, 2007.](https://mlanthology.org/iccv/2007/lord2007iccv-ussr/) doi:10.1109/ICCV.2007.4408969

BibTeX

@inproceedings{lord2007iccv-ussr,
  title     = {{USSR: A Unified Framework for Simultaneous Smoothing, Segmentation, and Registration of Multiple Images}},
  author    = {Lord, Nicholas A. and Ho, Jeffrey and Vemuri, Baba C.},
  booktitle = {IEEE/CVF International Conference on Computer Vision},
  year      = {2007},
  pages     = {1-6},
  doi       = {10.1109/ICCV.2007.4408969},
  url       = {https://mlanthology.org/iccv/2007/lord2007iccv-ussr/}
}