The "direct methods" achieve global image registration without explicit knowledge of feature correspondences. We employ the motion gradient constraint as the relation between the motion parameters and the measured image gradients. While this relation appears as a linear system of equations, for any motion model (other than a translation) we show that the underlying noise process is data-dependent, i.e., heteroscedastic, a fact which must be taken into account in the parameter estimation process. The improvement obtained using the adequate procedure is confirmed for the 2D rigid motion model through comparison with the traditional total least square approach.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Registration via direct methods: a statistical approach


    Contributors:
    Bride, J. (author) / Meer, P. (author)


    Publication date :

    2001-01-01


    Size :

    699482 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Registration via Direct Methods: A Statistical Approach

    Bride, J. / Meer, P. / IEEE | British Library Conference Proceedings | 2001


    Statistical Motion Mask and Sliding Registration

    Eiben, B / Tran, EH / Menten, MJ et al. | BASE | 2018

    Free access

    Results of a National Driver Registration Statistical Match

    K. R. Buck / D. A. Richmond / H. E. Timm | NTIS | 2007


    Algebraic Methods for Direct and Feature Based Registration of Diffusion Tensor Images

    Goh, A. / Vidal, R. | British Library Conference Proceedings | 2006


    Algebraic Methods for Direct and Feature Based Registration of Diffusion Tensor Images

    Goh, Alvina / Vidal, René | Springer Verlag | 2006

    Free access