Digital image correlation involves an inverse problem: A regularization scheme based on subset size constraint
文献类型：期刊论文
| 作者 | Zhan, Qin1; Yuan, Yuan1; Fan, Xiangtao1; Huang, Jianyong1; Xiong, Chunyang1; Yuan, Fan1 |
| 刊名 | Optics and Lasers in Engineering
 |
| 出版日期 | 2016 |
| 卷号 | 81页码:54-62 |
| 关键词 | RADIATIVE PROPERTIES MULTIPLE SCATTERING FRACTAL CLUSTERS CROSS-SECTIONS EM WAVES T-MATRIX AEROSOL PARTICLES SPHERES ABSORPTION |
| 通讯作者 | Huang, Jianyong (hjypku@gmail.com) |
| 英文摘要 | Digital image correlation (DIC) is essentially implicated in a class of inverse problem. Here, a regularization scheme is developed for the subset-based DIC technique to effectively inhibit potential ill-posedness that likely arises in actual deformation calculations and hence enhance numerical stability, accuracy and precision of correlation measurement. With the aid of a parameterized two-dimensional Butterworth window, a regularized subpixel registration strategy is established, in which the amount of speckle information introduced to correlation calculations may be weighted through equivalent subset size constraint. The optimal regularization parameter associated with each individual sampling point is determined in a self-adaptive way by numerically investigating the curve of 2-norm condition number of coefficient matrix versus the corresponding equivalent subset size, based on which the regularized solution can eventually be obtained. Numerical results deriving from both synthetic speckle images and actual experimental images demonstrate the feasibility and effectiveness of the set of newly-proposed regularized DIC algorithms. © 2016 Elsevier Ltd. All rights reserved. |
| 学科主题 | Optics |
| 类目[WOS] | Optics |
| 收录类别 | SCI ; EI |
| 语种 | 英语 |
| WOS记录号 | WOS:20161002054237 |
| 源URL | [http://ir.radi.ac.cn/handle/183411/39270]  |
| 专题 | 遥感与数字地球研究所_SCI/EI期刊论文_期刊论文 |
| 作者单位 | 1. Key Laboratory of Digital Earth, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China 2. College of Ocean Science and Engineering, Shanghai Maritime University, Shanghai, China 3. College of Engineering, Peking University, Beijing, China 4. Department of Biomedical Engineering, Duke University, Durham 5.NC, United States |
| 推荐引用方式 GB/T 7714 | Zhan, Qin,Yuan, Yuan,Fan, Xiangtao,et al. Digital image correlation involves an inverse problem: A regularization scheme based on subset size constraint[J]. Optics and Lasers in Engineering,2016,81:54-62. |
| APA | Zhan, Qin,Yuan, Yuan,Fan, Xiangtao,Huang, Jianyong,Xiong, Chunyang,&Yuan, Fan.(2016).Digital image correlation involves an inverse problem: A regularization scheme based on subset size constraint.Optics and Lasers in Engineering,81,54-62. |
| MLA | Zhan, Qin,et al."Digital image correlation involves an inverse problem: A regularization scheme based on subset size constraint".Optics and Lasers in Engineering 81(2016):54-62. |
入库方式： OAI收割
来源：遥感与数字地球研究所
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