Abstract：Feature points in images are commonly used for image registration. Feature points can be classified as in narrow sense and in broad sense. Feature Points in Broad Sense (FPBS) can be defined in different ways. A new definition of FPBS is proposed that is reasonable for image registration. The FPBS can be detected automatically by the use of multi-scale wavelet transform and a few additional restrictions that control the complexity and nonperiodicity of local regions. After feature point sets are extracted separately
from the two images under consideration, the relation between them is then established by a two-stage matching algorithm. The registration transform is found by minimizing the Root Mean Square Error (RMSE) of the control points. An iterative optimization
mechanism is used to refine the registration. Several experimental results of image registration can illustrate the performance of the
method.
王东峰; 张丽飞; 刘小军; 邹谋炎. 基于广义特征点匹配的全自动图像配准[J]. 电子与信息学报, 2005, 27(7): 1013-1016 .
Wang Dong-feng; Zhang Li-fei; Liu Xiao-jun; Zou Mou-yan. Automatic Image Registration Based on Matching of Feature Points in Broad Sense. , 2005, 27(7): 1013-1016 .
2005, Vol. 27 
