Remote sensing image change detection using particle swarm optimization algorithm

Cehui Xuebao/Acta Geodaetica et Cartographica Sinica

Volumn 41, Issue 6, 2012, Pages

  Dai, Qin ^a   Liu, Jianbo ^a   Liu, Shibin ^a  

^a CENTER FOR EARTH OBSERVATION AND DIGITAL EARTH   (China)

Author keywords

Change detection; Multi temporal remote sensing image; Particle swarm optimization algorithm

Indexed keywords

BEIJING AREA; CHANGE DETECTION; HIGH PRECISION; INFORMATION EXTRACTION; LAND-COVER CHANGE; MAXIMUM LIKELIHOOD METHODS; MULTI-TEMPORAL REMOTE SENSING; PARTICLE SWARM OPTIMIZATION ALGORITHM; PSO ALGORITHMS; REMOTE SENSING IMAGES;

IMAGE RECONSTRUCTION; PARTICLE SWARM OPTIMIZATION (PSO); REMOTE SENSING; SIGNAL DETECTION;

ALGORITHMS;

EID: 84872532052     PISSN: 10011595     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (17)

1. ZHONG Jiaqiang, WANG Runsheng. Multitemporal Remote Sensing Image Change Detection Based on Adaptive Parameter Estimation [J]. Acta Geodaetica et Cartographica Sinica, 2005, 34(4): 331-336.
2. CUI Weihong, SHI Wenzhong, LI Xiaojuan. Development of A Feature Based Saptial-temporal Data Model for Land Use Change Dynamic Monitoring [J]. Acta Geodaetica et Cartographica Sinica, 2004, 33(2): 138-144.
3. LU D, MAUSEL P E, BRONDIZIO E, et al. Change Detection Techniques [J]. International Journal of Remote Sensing, 2004, 25(12): 2365-2407.
4. HAME T, HEILER I, MIGUEL-AYANZ J S. An Unsupervised Change and Recognition System for Forestry [J]. International Journal of Remote Sensing, 1998, 19(6): 1079-1099.
5. SINGH A. Digital Change Detection Techniques Using Remotely-sensed Data [J]. International Journal of Remote Sensing, 1989, 10(6): 989-1003.
6. NEMMOUR H, CHIBANI Y. Fuzzy Neural Network Architecture for Change Detection in Remotely Sensed Imagery [J]. International Journal of Remote Sensing, 2006, 27(4): 705-717.
7. MA Jianwen, TIAN Guoliang, WANG Changyao, et al. Review of the Development of Remote Sensing Change Detection Technology [J]. Advance in Earth Science, 2004, 19(2): 192-196.
8. DAI X L, KHORRAM S. Remotely Sensed Change Detection Based on Artificial Neural Networks [J]. Photogrammetric Engineering & Remote Sensing, 1999, 65(10): 1187-1194.
9. PENG Xiyuan, PENG Yu, DAI Yufeng. Swarm Intelligence Theory and Applications [J]. Acta Electronica Sinica, 2003, 31(12): 1983-1988.
10. KENNEDY J. Particle Warm Optimizations [C]//Proceedings of the 1995 IEEE International Conference on Neural Networks. Piscataway. Perth: IEEE Service Center, 1995: 1942-1948.
11. LIU Xiaoping, LI Xia, PENG Xiaojuan, et al. Swarm Intelligence for Classification of Remote Sensing Data [J]. Science China: D, 2007, 37(10): 1401-1408.
12. HOLDEN N P, FREITAS A A. A Hybrid PSO/ACO Algorithm for Classification [C]//Proceedings of the 2007 GECCO Conference Companion on Genetic and Evolutionary Computation. London: [s.n.], 2007: 2745-2750.
13. BRATTON D, KENNEDY J. Defining a Standard for Particle Swarm Optimization [C]//Proceedings of the 2007 IEEE Swarm Intelligent Symposium. Honolulu: IEEE, 2007: 120-127.
14. PARPINELLI R S, LOPES H S, FREITAS A A. Data Mining with an Ant Colony Optimization Algorithm [J]. IEEE Transactions on Evolutionary Computation, 2002, 6(4): 321-332.
15. QUINLAN J R. C4.5: Programs for Machine Learning [M]. San Francisco: Morgan Kaufmann, 1993.
16. FRANK E, WITTEN I H. Generating Accurate Rule Sets without Global Optimization [C]//Fifteenth International Conference on Machine Learning. San Francisco: Morgan Kaufmann, 1998: 144-151.
17. DAI Qin, LIU Jianbo, LIU Shibin. Analysis of Remote Sensing Information Extraction Using Swarm Intelligence Method [J]. Computer Engineering and Applications, 2011, 47(4): 13-16.