TY - GEN
T1 - An evolutionary approach for image registration
AU - Zhang, Jing
AU - Zhou, Aimin
AU - Zhang, Guixu
PY - 2012
Y1 - 2012
N2 - Image registration plays an important role in many real-world applications such as remote sensing. A key issue of image registration is to find the hidden relationship between the input image and the reference image. In many cases, the hidden relationship is presented by a coordinate transformation matrix. Therefore, an image registration can be formulated as an optimization problem. In this paper, we propose to use evolutionary algorithms to optimize the transformation matrix. Instead of finding an optimal mapping between each pixel in the input and reference images, some local image features which are expressed as control points, are firstly extracted from the two images. An evolutionary algorithm is then applied to find the optimal mapping between the control points. Finally, the input image is registrated by the optimal transformation. The proposed approach is applied to some remote sensing images and the statistical results show that our approach is promising for dealing with image registration.
AB - Image registration plays an important role in many real-world applications such as remote sensing. A key issue of image registration is to find the hidden relationship between the input image and the reference image. In many cases, the hidden relationship is presented by a coordinate transformation matrix. Therefore, an image registration can be formulated as an optimization problem. In this paper, we propose to use evolutionary algorithms to optimize the transformation matrix. Instead of finding an optimal mapping between each pixel in the input and reference images, some local image features which are expressed as control points, are firstly extracted from the two images. An evolutionary algorithm is then applied to find the optimal mapping between the control points. Finally, the input image is registrated by the optimal transformation. The proposed approach is applied to some remote sensing images and the statistical results show that our approach is promising for dealing with image registration.
KW - affine transformation
KW - evolutionary optimization
KW - image registration
KW - remote sensing
UR - https://www.scopus.com/pages/publications/84868269799
U2 - 10.1007/978-3-642-34289-9_36
DO - 10.1007/978-3-642-34289-9_36
M3 - 会议稿件
AN - SCOPUS:84868269799
SN - 9783642342882
T3 - Communications in Computer and Information Science
SP - 321
EP - 330
BT - Computational Intelligence and Intelligent Systems - 6th International Symposium, ISICA 2012, Proceedings
T2 - 6th International Symposium on Intelligence Computation and Applications, ISICA 2012
Y2 - 27 October 2012 through 28 October 2012
ER -