Knowledge Commons of Institute of Automation，CAS
| A total variation based nonrigid image registration by combining parametric and non-parametric transformation models | |
Hu, Wenrui ; Xie, Yuan; Li, Lin; Zhang, Wensheng
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| 发表期刊 | NEUROCOMPUTING
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| 2014-11-20 | |
| 卷号 | 144页码:222-237 |
| 文章类型 | Article |
| 摘要 | To overcome the conflict between the global robustness and the local accuracy of dense nonrigid image registration, we propose a union registration approach by combining parametric and non-parametric transformation models. On one hand, to guarantee the robustness, we constrain the displacement field phi using a mapping difference metric between the B-spline parametric space psi and the non-parametric transformation space (Phi. On the other hand, to correct the densely and highly localized geometrical distortions, we introduce a total variation (TV) regularization term for the displacement field phi. Accounting for the effect of spatially varying intensity distortions, the residual complexity (RC) is used as the similarity metric. Moreover, to solve the proposed union nonrigid registration, which is a composite convex optimization problem by the smooth l(2) term and the non-smooth l(2) term (TV), we design a two-stage algorithm using split Bregman iteration. Experiments with both synthetic and real images from different domains illustrate that this approach can capture the local details of transformation accurately and effectively while being robust to the spatially varying intensity distortions. (C) 2014 Elsevier B.V. All rights reserved. |
| 关键词 | Nonrigid Registration Free-form Deformation Non-parametric Transformation Total Variation Split Bregman Iteration |
| WOS标题词 | Science & Technology ; Technology |
| 关键词[WOS] | FREE-FORM DEFORMATIONS ; OPTICAL-FLOW ; ALGORITHMS |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS研究方向 | Computer Science |
| WOS类目 | Computer Science, Artificial Intelligence |
| WOS记录号 | WOS:000341677800022 |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://ir.ia.ac.cn/handle/173211/8069 |
| 专题 | 中科院工业视觉智能装备工程实验室_精密感知与控制 |
| 作者单位 | Chinese Acad Sci, Inst Automat, State Key Lab Intelligent Control & Management Co, Beijing 100190, Peoples R China |
| 第一作者单位 | 中国科学院自动化研究所 |
| 推荐引用方式 GB/T 7714 | Hu, Wenrui,Xie, Yuan,Li, Lin,et al. A total variation based nonrigid image registration by combining parametric and non-parametric transformation models[J]. NEUROCOMPUTING,2014,144:222-237. |
| APA | Hu, Wenrui,Xie, Yuan,Li, Lin,&Zhang, Wensheng.(2014).A total variation based nonrigid image registration by combining parametric and non-parametric transformation models.NEUROCOMPUTING,144,222-237. |
| MLA | Hu, Wenrui,et al."A total variation based nonrigid image registration by combining parametric and non-parametric transformation models".NEUROCOMPUTING 144(2014):222-237. |
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| 文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
| A total variation ba（20168KB） | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 | |
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