| 海岛礁光学和雷达影像基于改进非子采样小波变换的自动配准 |
| |
| 作者姓名： | SHI Wei SU Fenzhen WANG Ruirui LU Yongduo |
| |
| 作者单位： | Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;Collaborative Innovation Center of South China Sea Studies, Nanjing University, Nanjing 210093, China;Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;Collaborative Innovation Center of South China Sea Studies, Nanjing University, Nanjing 210093, China;Beijing Forestry University, Beijing 100083, China;National Marine Environmental Forecasting Center, State Oceanic Administration, Beijing 100081, China |
| |
| 基金项目： | The National Natural Science Foundation of China under contract No. 41271409; the National Key Technology Research and Development Program under contract No. 2011BAH23B00; the National High Technology Research and Development Program (863 Program) of China under contract No. 2012AA12A406. |
| |
| 摘 要： | Homologous feature point extraction is a key problem in the optical and synthetic aperture radar （SAR） image registration for islands. A new feature point extraction method using a threshold shrink operator and non-subsampled wavelet transform （TSO-NSWT） for optical and SAR image registration was proposed. Moreover, the matching for this proposed feature was different from the traditional feature matching strategies and was performed using a similarity measure computed from neighborhood circles in low-frequency bands. Then, a number of reliably matched couples with even distributions were obtained, which assured the accuracy of the registration. Application of the proposed algorithm to SPOT-5 （multi-spectral） and YG-1 （SAR） images showed that a large number of accurately matched couples could be identified. Additionally, both of the root mean square error （RMSE） patterns of the registration parameters computed based on the TSO-NSWT algorithm and traditional NSWT algorithm were analyzed and compared, which further demonstrated the effectiveness of the proposed algorithm. The algorithm can supply the crucial step for island image registration and island recognition.
|
| 关 键 词： | 图像配准 小波变换 SAR 下采样 光学 基础 海岛 合成孔径雷达 |
| 收稿时间： | 2012/12/5 0:00:00 |
| 修稿时间： | 2013/9/22 0:00:00 |
Optical and SAR image registration based on improved nonsubsampled wavelet transform for sea islands |
| |
| SHI Wei,SU Fenzhen,WANG Ruirui,LU Yongduo.Optical and SAR image registration based on improved nonsubsampled wavelet transform for sea islands[J].Acta Oceanologica Sinica,2014,33(5):86-95. |
| |
| Authors: | SHI Wei SU Fenzhen WANG Ruirui and LU Yongduo |
| |
| Institution: | 1.Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;Collaborative Innovation Center of South China Sea Studies, Nanjing University, Nanjing 210093, China2.Beijing Forestry University, Beijing 100083, China3.National Marine Environmental Forecasting Center, State Oceanic Administration, Beijing 100081, China |
| |
| Abstract: | Homologous feature point extraction is a key problem in the optical and synthetic aperture radar (SAR) image registration for islands. A new feature point extraction method using a threshold shrink operator and non-subsampled wavelet transform (TSO-NSWT) for optical and SAR image registration was proposed. Moreover, the matching for this proposed feature was different from the traditional feature matching strategies and was performed using a similarity measure computed from neighborhood circles in low-frequency bands. Then, a number of reliably matched couples with even distributions were obtained, which assured the accuracy of the registration. Application of the proposed algorithm to SPOT-5 (multi-spectral) and YG-1 (SAR) images showed that a large number of accurately matched couples could be identified. Additionally, both of the root mean square error (RMSE) patterns of the registration parameters computed based on the TSO-NSWT algorithm and traditional NSWT algorithm were analyzed and compared, which further demonstrated the effectiveness of the proposed algorithm. The algorithm can supply the crucial step for island image registration and island recognition. |
| |
| Keywords: | image registration islands South China Sea wavelet transform threshold shrink operator |
| 本文献已被 CNKI 维普 SpringerLink 等数据库收录！ |
| 点击此处可从《海洋学报(英文版)》浏览原始摘要信息 |
| 点击此处可从《海洋学报(英文版)》下载免费的PDF全文 |
|
