Intensity based nonparametric image registration

Authors:
Peihua Qiu;Chen Xing
Affiliations:
University of Minnesota, Minneapolis, MN, USA;University of Minnesota, Minneapolis, MN, USA
Venue:
Proceedings of the international conference on Multimedia information retrieval
Year:
2010

Citing 5
Cited 2

Computing Large Deformation Metric Mappings via Geodesic Flows of Diffeomorphisms

International Journal of Computer Vision
On Image Registration in Magnetic Resonance Imaging

BMEI '08 Proceedings of the 2008 International Conference on BioMedical Engineering and Informatics - Volume 02
A nonparametric procedure for blind image deblurring

Computational Statistics & Data Analysis
Directly manipulated free-form deformation image registration

IEEE Transactions on Image Processing
Fair: Flexible Algorithms for Image Registration

Fair: Flexible Algorithms for Image Registration

Multiscaled combination of MR and SPECT images in neuroimaging: A simplex method based variable-weight fusion

Computer Methods and Programs in Biomedicine
Feature based image registration using non-degenerate pixels

Signal Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

Image registration is used widely in applications for mapping one image to another. Existing image registration methods are either feature-based or intensity-based. Feature-based methods first extract relevant image features, and then find a geometrical transformation that best matches the two corresponding sets of features extracted from the two images. Because identification and extraction of image features is often a challenging and time-consuming process, intensity-based image registration, by which the mapping transformation is estimated directly from the observed image intensities of the two images, has received much attention recently. In the literature, most existing intensity-based image registration methods require a parametric form of the mapping transformation, which is restrictive for certain applications. In this paper, we propose an intensity-based image registration method without requiring such a parametric form. By this method, the mapping transformation can be nonparametric, and it can even be discontinuous at certain places in the design space. Numerical examples show that it is effective in various applications.