Implicit similarity: a new approach to multi-sensor image registration

Y. Keller, Amir Averbuch

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

Abstract

This paper presents an implicit similarity-based approach to registration of significantly dissimilar images, acquired by sensors at different modalities. The proposed algorithm introduces a robust matching criterion by aligning the locations of gradient maxima. The alignment is formulated as a parametric variational optimization problem, which is solved iteratively by considering the intensities of a single image. The location of the maxima of the second image's gradient are used as initialization. We are able to robustly estimate affine and projective global motions using 'coarse to fine' processing, even when the images are characterized by complex space varying intensity transformations. Finally, we present the registration of real images, which were taken by multi-sensor and multi-modality using affine and projective motion models.
Original languageAmerican English
Title of host publicationComputer Vision and Pattern Recognition, 2003. Proceedings. 2003 IEEE Computer Society Conference on
PublisherIEEE
StatePublished - 2003

Bibliographical note

Place of conference:USA

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