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题名:
Coregistration based on stochastic parallel gradient descent algorithm for SAR interferometry
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
学科分类: Algorithms - Data handling - Gradient methods - Interferometry - Stochastic models - Stochastic systems
DOI: 10.1080/2150704X.2014.986304
通讯作者: Long, Xuejun
文章类型: 期刊论文
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.
收录类别: Ei
语种: 英语
ISSN号: 2150704X
Citation statistics:
内容类型: 期刊论文
URI标识: http://ir.ioe.ac.cn/handle/181551/4145
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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

Recommended Citation:
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.
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