A probabilistic demons algorithm for texture-rich image registration

Di Yang*, Hongdong Li

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    1 Citation (Scopus)

    Abstract

    Demons algorithm has attracted considerable attention from the image processing community for registering (i.e., matching/aligning) deformable objects or images. It is observed that this algorithm is particularly successful when it applies to nonrigid object having homogenous region, but often fails when the object of interest is rich in texture. This is mainly because the Demons algorithm tends to overfit the many spurious edges inside the texture-rich region, consequently leading to erroneous thermodynamic 'forces'. In this paper, we describe a probabilistic Demons algorithm that overcomes this problem. Our key idea is to re-formulate the deformable registration problem in Bayesian statistics framework. The result is a new and more robust Demons algorithm able to capture the essence (e.g., the mass) of a deformable image/object even it is rich in texture. This will significantly expand the applicable scopes of the traditional Demons algorithm. We give encouraging experimental results on real test images.

    Original languageEnglish
    Title of host publication2009 IEEE International Conference on Image Processing, ICIP 2009 - Proceedings
    PublisherIEEE Computer Society
    Pages161-164
    Number of pages4
    ISBN (Print)9781424456543
    DOIs
    Publication statusPublished - 2009
    Event2009 IEEE International Conference on Image Processing, ICIP 2009 - Cairo, Egypt
    Duration: 7 Nov 200910 Nov 2009

    Publication series

    NameProceedings - International Conference on Image Processing, ICIP
    ISSN (Print)1522-4880

    Conference

    Conference2009 IEEE International Conference on Image Processing, ICIP 2009
    Country/TerritoryEgypt
    CityCairo
    Period7/11/0910/11/09

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