Coregistration based on stochastic parallel gradient descent algorithm for SAR interferometry
文献类型：期刊论文
| 作者 | Long, Xuejun1,2,3; Fu, Sihua3; Yu, Qifeng3; Wang, Sanhong4; Qi, Bo1,2; Ren, Ge1,2 |
| 刊名 | Remote Sensing Letters
 |
| 出版日期 | 2014 |
| 卷号 | 5期号:11页码:991-1000 |
| ISSN号 | 2150704X |
| 通讯作者 | Long, Xuejun |
| 中文摘要 | The coregistration of complex image pairs is a very important step in interferometric synthetic aperture radar (InSAR) data processing. This article proposes a coregistration method based on the stochastic parallel gradient descent (SPGD) algorithm. Stochastic parallel perturbations are imposed on the translation coefficients of the polynomial coregistration model to make the performance evaluation function converge to a global extremum, which allows the translation coefficients to be obtained, and then the coregistration is achieved after resampling. Data processing of images from Kashgar and Mount Etna show that the proposed method is effective and robust. Furthermore, a series of experiments is designed to evaluate the convergence characteristics of the proposed method, which indicates that it has a stable convergence process and good robustness. |
| 英文摘要 | The coregistration of complex image pairs is a very important step in interferometric synthetic aperture radar (InSAR) data processing. This article proposes a coregistration method based on the stochastic parallel gradient descent (SPGD) algorithm. Stochastic parallel perturbations are imposed on the translation coefficients of the polynomial coregistration model to make the performance evaluation function converge to a global extremum, which allows the translation coefficients to be obtained, and then the coregistration is achieved after resampling. Data processing of images from Kashgar and Mount Etna show that the proposed method is effective and robust. Furthermore, a series of experiments is designed to evaluate the convergence characteristics of the proposed method, which indicates that it has a stable convergence process and good robustness. |
| 学科主题 | Algorithms - Data handling - Gradient methods - Interferometry - Stochastic models - Stochastic systems |
| 收录类别 | EI |
| 语种 | 英语 |
| 源URL | [http://ir.ioe.ac.cn/handle/181551/4145]  |
| 专题 | 光电技术研究所_光电工程总体研究室（一室） |
| 作者单位 | 1.Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu, Sichuan, China 2.Beam Control Laboratory, Chinese Academy of Sciences, Chengdu, Sichuan, China 3.College of Optoelectric Science and Engineering, National University of Defense Technology, Changsha, Hunan, China 4.Taiyuan Satellite Launch Center, Taiyuan, Shanxi, China |
| 推荐引用方式 GB/T 7714 | Long, Xuejun,Fu, Sihua,Yu, Qifeng,et al. Coregistration based on stochastic parallel gradient descent algorithm for SAR interferometry[J]. Remote Sensing Letters,2014,5(11):991-1000. |
| APA | Long, Xuejun,Fu, Sihua,Yu, Qifeng,Wang, Sanhong,Qi, Bo,&Ren, Ge.(2014).Coregistration based on stochastic parallel gradient descent algorithm for SAR interferometry.Remote Sensing Letters,5(11),991-1000. |
| MLA | Long, Xuejun,et al."Coregistration based on stochastic parallel gradient descent algorithm for SAR interferometry".Remote Sensing Letters 5.11(2014):991-1000. |
入库方式： OAI收割
来源：光电技术研究所
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