A self-referencing level-set method for image reconstruction from sparse Fourier samples

Jong Chul Ye, Y. Bresler, P. Moulin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We address image estimation from sparse Fourier samples. The problem is formulated as joint estimation of the supports of unknown sparse objects in the image, and pixel values on these supports. The domain and the pixel values are alternately estimated using the level-set method and the conjugate gradient method, respectively. Our level-set evolution shows a unique switching behavior, which stabilizes the level-set evolution. Furthermore, the trade-off between the stability and the speed of evolution can be easily controlled by the number of the conjugate gradient steps, hence removing the re-initialization steps in conventional level set approaches.

Original languageEnglish (US)
Title of host publicationProceedings - IEEE Workshop on Variational and Level Set Methods in Computer Vision, VLSM 2001
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages171-178
Number of pages8
ISBN (Electronic)076951278X, 9780769512785
DOIs
StatePublished - Jan 1 2001
EventIEEE Workshop on Variational and Level Set Methods in Computer Vision, VLSM 2001 - Vancouver, Canada
Duration: Jul 13 2001 → …

Publication series

NameProceedings - IEEE Workshop on Variational and Level Set Methods in Computer Vision, VLSM 2001

Other

OtherIEEE Workshop on Variational and Level Set Methods in Computer Vision, VLSM 2001
CountryCanada
CityVancouver
Period7/13/01 → …

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Vision and Pattern Recognition

Fingerprint Dive into the research topics of 'A self-referencing level-set method for image reconstruction from sparse Fourier samples'. Together they form a unique fingerprint.

  • Cite this

    Ye, J. C., Bresler, Y., & Moulin, P. (2001). A self-referencing level-set method for image reconstruction from sparse Fourier samples. In Proceedings - IEEE Workshop on Variational and Level Set Methods in Computer Vision, VLSM 2001 (pp. 171-178). [938896] (Proceedings - IEEE Workshop on Variational and Level Set Methods in Computer Vision, VLSM 2001). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/VLSM.2001.938896