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

Yosi Keller*, Amir Averbuch

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

Abstract

This paper presents an implicit similarity-based approach to registration of significantly dissimilar images, acquired by sensors of 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 locations of the maxima of the second image's gradient are used as initialization. We were 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 languageEnglish
Pages (from-to)II/543-II/548
JournalProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Volume2
StatePublished - 2003
Event2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2003 - Madison, WI, United States
Duration: 18 Jun 200320 Jun 2003

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