TY - JOUR
T1 - Remote sensing image registration via active contour model
AU - Yang, Michael Ying
AU - Gao, Xin
PY - 2009/4/1
Y1 - 2009/4/1
N2 - Image registration is the process by which we determine a transformation that provides the most accurate match between two images. The search for the matching transformation can be automated with the use of a suitable metric, but it can be very time-consuming and tedious. In this paper, we introduce a registration algorithm that combines active contour segmentation together with mutual information. Our approach starts with a segmentation procedure. It is formed by a novel geometric active contour, which incorporates edge knowledge, namely Edgeflow, into active contour model. Two edgemap images filled with closed contours are obtained. After ruling out mismatched curves, we use mutual information (MI) as a similarity measure to register two edgemap images. Experimental results are provided to illustrate the performance of the proposed registration algorithm using both synthetic and multisensor images. Quantitative error analysis is also provided and several images are shown for subjective evaluation.
AB - Image registration is the process by which we determine a transformation that provides the most accurate match between two images. The search for the matching transformation can be automated with the use of a suitable metric, but it can be very time-consuming and tedious. In this paper, we introduce a registration algorithm that combines active contour segmentation together with mutual information. Our approach starts with a segmentation procedure. It is formed by a novel geometric active contour, which incorporates edge knowledge, namely Edgeflow, into active contour model. Two edgemap images filled with closed contours are obtained. After ruling out mismatched curves, we use mutual information (MI) as a similarity measure to register two edgemap images. Experimental results are provided to illustrate the performance of the proposed registration algorithm using both synthetic and multisensor images. Quantitative error analysis is also provided and several images are shown for subjective evaluation.
KW - ITC-ISI-JOURNAL-ARTICLE
UR - https://ezproxy2.utwente.nl/login?url=https://library.itc.utwente.nl/login/2009/isi/yang_rem.pdf
UR - https://ezproxy2.utwente.nl/login?url=https://doi.org/10.1016/j.aeue.2008.01.003
U2 - 10.1016/j.aeue.2008.01.003
DO - 10.1016/j.aeue.2008.01.003
M3 - Article
VL - 63
SP - 227
EP - 234
JO - AEÜ International journal of electronics and communications
JF - AEÜ International journal of electronics and communications
SN - 1434-8411
IS - 4
ER -