Ensemble Registration of Multisensor Images by a Variational Bayesian Approach
Ensemble Registration of Multisensor Images by a Variational Bayesian Approach
复制标题
通过变分贝叶斯方法对多传感器图像进行整体配准
DOI：
10.1109/jsen.2014.2315838
复制
发表时间：
2014-04
影响因子：
4.3
通讯作者：
Henry Leung
中科院分区：
文献类型：
--
作者：
Hao Zhu;Yongfu Li;Jimin Yu;Henry Leung
In this paper, a novel image registration method, called ensemble image registration, is proposed. We use an infinite Gaussian mixture model (IGMM), which is based on a joint Gaussian mixture model and a Dirichlet process (DP), to model the joint intensity scatter plot (JISP) of the unregistered images. The DP is the cornerstone of nonparametric Bayesian statistics, and has capability of determining a proper number of mixing components. To simultaneously register a group of images, the cost function of reducing the dispersion in the JISP is preformed by a Bayesian method using IGMM. A variational Bayesian framework is developed to inference the posterior distribution of the parameters in the IGMM. To evaluate the performance of the proposed method, experiments of ensemble image registration are presented. The results show that the proposed method has improved performance compared with conventional methods.
登录
查看更多内容
DOI：
--
发表时间：
1994
期刊：
--
影响因子：
--
作者：
Lawrence Berkeley Laboratory;Lindsay Schachinger
通讯作者：
Lawrence Berkeley Laboratory;Lindsay Schachinger
影响因子：
2.5
作者：
Barron, A;Rissanen, J;Yu, B
通讯作者：
Yu, B
影响因子：
1.3
作者：
Woods, RP;Grafton, ST;Mazziotta, JC
通讯作者：
Mazziotta, JC
影响因子：
4.4
作者：
Neemuchwala, H;Hero, A;Carson, P
通讯作者：
Carson, P
影响因子：
6.8
作者：
AKAIKE, H
通讯作者：
AKAIKE, H