Novel Registration and Fusion Algorithm for Multimodal Railway Images with Different Field of Views
Objects intruding high-speed railway clearance do great threat to running trains. In order to improve accuracy of railway intrusion detection, an automatic multimodal registration and fusion algorithm for infrared and visible images with different field of views is presented. The ratio of the neares...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2018-01-01
|
| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2018/7836169 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832548443523907584 |
|---|---|
| author | Baoqing Guo Xingfang Zhou Yingzi Lin Liqiang Zhu Zujun Yu |
| author_facet | Baoqing Guo Xingfang Zhou Yingzi Lin Liqiang Zhu Zujun Yu |
| author_sort | Baoqing Guo |
| collection | DOAJ |
| description | Objects intruding high-speed railway clearance do great threat to running trains. In order to improve accuracy of railway intrusion detection, an automatic multimodal registration and fusion algorithm for infrared and visible images with different field of views is presented. The ratio of the nearest to next nearest distance, geometric, similar triangle, and RANSAC constraints are used to refine the matching SURF feature points successively. Correct matching points are accumulated with multiframe to overcome the insufficient matching points in single image pair. After being registered, an improved Contourlet transform fusion algorithm combined with total variation and local region energy is proposed. Inverse Contourlet transform to low frequency subband coefficient fused with total variation model and high frequency subband coefficients fused with local region energy is used to reconstruct the fused image. The comparison to other 4 popular fusion methods shows that our algorithm has the best comprehensive performance for multimodal railway image fusion. |
| format | Article |
| id | doaj-art-f9e3d570fc8245cfbb935c2f34b5dba0 |
| institution | Kabale University |
| issn | 0197-6729 2042-3195 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-f9e3d570fc8245cfbb935c2f34b5dba02025-02-03T06:14:12ZengWileyJournal of Advanced Transportation0197-67292042-31952018-01-01201810.1155/2018/78361697836169Novel Registration and Fusion Algorithm for Multimodal Railway Images with Different Field of ViewsBaoqing Guo0Xingfang Zhou1Yingzi Lin2Liqiang Zhu3Zujun Yu4School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing 100044, ChinaKey Laboratory of Vehicle Advanced Manufacturing, Measuring and Control Technology (Beijing Jiaotong University), Ministry of Education, Beijing 100044, ChinaDepartment of Mechanical and Industrial Engineering, Northeastern University, Boston, MA 02115, USASchool of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing 100044, ChinaSchool of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing 100044, ChinaObjects intruding high-speed railway clearance do great threat to running trains. In order to improve accuracy of railway intrusion detection, an automatic multimodal registration and fusion algorithm for infrared and visible images with different field of views is presented. The ratio of the nearest to next nearest distance, geometric, similar triangle, and RANSAC constraints are used to refine the matching SURF feature points successively. Correct matching points are accumulated with multiframe to overcome the insufficient matching points in single image pair. After being registered, an improved Contourlet transform fusion algorithm combined with total variation and local region energy is proposed. Inverse Contourlet transform to low frequency subband coefficient fused with total variation model and high frequency subband coefficients fused with local region energy is used to reconstruct the fused image. The comparison to other 4 popular fusion methods shows that our algorithm has the best comprehensive performance for multimodal railway image fusion.http://dx.doi.org/10.1155/2018/7836169 |
| spellingShingle | Baoqing Guo Xingfang Zhou Yingzi Lin Liqiang Zhu Zujun Yu Novel Registration and Fusion Algorithm for Multimodal Railway Images with Different Field of Views Journal of Advanced Transportation |
| title | Novel Registration and Fusion Algorithm for Multimodal Railway Images with Different Field of Views |
| title_full | Novel Registration and Fusion Algorithm for Multimodal Railway Images with Different Field of Views |
| title_fullStr | Novel Registration and Fusion Algorithm for Multimodal Railway Images with Different Field of Views |
| title_full_unstemmed | Novel Registration and Fusion Algorithm for Multimodal Railway Images with Different Field of Views |
| title_short | Novel Registration and Fusion Algorithm for Multimodal Railway Images with Different Field of Views |
| title_sort | novel registration and fusion algorithm for multimodal railway images with different field of views |
| url | http://dx.doi.org/10.1155/2018/7836169 |
| work_keys_str_mv | AT baoqingguo novelregistrationandfusionalgorithmformultimodalrailwayimageswithdifferentfieldofviews AT xingfangzhou novelregistrationandfusionalgorithmformultimodalrailwayimageswithdifferentfieldofviews AT yingzilin novelregistrationandfusionalgorithmformultimodalrailwayimageswithdifferentfieldofviews AT liqiangzhu novelregistrationandfusionalgorithmformultimodalrailwayimageswithdifferentfieldofviews AT zujunyu novelregistrationandfusionalgorithmformultimodalrailwayimageswithdifferentfieldofviews |