TY - GEN
T1 - Robust multi-sensor image registration using pixel migration
AU - Keller, Y.
AU - Averbuch, A.
N1 - Publisher Copyright:
© 2002 IEEE.
PY - 2002
Y1 - 2002
N2 - This paper presents an energy minimization 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. This implicit matching criterion is achieved while utilizing the full spatial information, without the need to use invariant image representations. 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. These cause current state-ofthe- Art algorithms to fail. Finally, we present the registration of real images, which were taken by multi-sensor and multi-modality using affine and projective motion models.
AB - This paper presents an energy minimization 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. This implicit matching criterion is achieved while utilizing the full spatial information, without the need to use invariant image representations. 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. These cause current state-ofthe- Art algorithms to fail. Finally, we present the registration of real images, which were taken by multi-sensor and multi-modality using affine and projective motion models.
UR - http://www.scopus.com/inward/record.url?scp=33745599226&partnerID=8YFLogxK
U2 - 10.1109/SAM.2002.1191008
DO - 10.1109/SAM.2002.1191008
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AN - SCOPUS:33745599226
T3 - Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop
SP - 100
EP - 104
BT - 2002 IEEE Sensor Array and Multichannel Signal Processing Workshop Proceedings, SAME 2002
PB - IEEE Computer Society
T2 - IEEE Sensor Array and Multichannel Signal Processing Workshop, SAME 2002
Y2 - 4 August 2002 through 6 August 2002
ER -