电子学报 ›› 2018, Vol. 46 ›› Issue (10): 2384-2390.DOI: 10.3969/j.issn.0372-2112.2018.10.011
所属专题: 机器学习—特征选择
周光兵, 宋华军, 吴玉兴, 任鹏
收稿日期:
2017-03-27
修回日期:
2017-09-26
出版日期:
2018-10-25
通讯作者:
作者简介:
基金资助:
ZHOU Guang-bing, SONG Hua-jun, WU Yu-xing, REN Peng
Received:
2017-03-27
Revised:
2017-09-26
Online:
2018-10-25
Published:
2018-10-25
Corresponding author:
Supported by:
摘要: 3D图像刚性配准旨在将一个图像映射到另一个具有相同场景的图像上,已经在医学诊断和其它领域中得到了广泛的应用.已有的方法大都基于特征点和针对特定的约束条件,带来了特征选择耗时多,随机性强,而且约束条件使用不灵活等问题.针对这些问题,提出直接使用图像灰度值的无特征3D刚性配准方法.该方法使用泰勒展开式和最小二乘法直接计算待配准图像的变换参数,并且使用较少的数据点完成快速的配准.实验结果表明,提出的算法获得较高的精度,并且使用少量的数据仍可以有效计算,这一特性使得它在大数据3D图像应用中更有吸引力.
中图分类号:
周光兵, 宋华军, 吴玉兴, 等. 一种非特征的3D图像快速刚性配准方法[J]. 电子学报, 2018, 46(10): 2384-2390.
ZHOU Guang-bing, SONG Hua-jun, WU Yu-xing, et al. A Non-Feature Fast 3D Rigid-Body Image Registration Method[J]. Acta Electronica Sinica, 2018, 46(10): 2384-2390.
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