光谱学与光谱分析 |
|
|
|
|
|
Classification of Wetlands in Multispectral Remote Sensing Image Based on HPSO and FCM |
JIANG Wei-guo1,2,CHEN Qiang1,2,GUO Ji3,TANG Hong1,2*,LI Xue1,2 |
1. State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China 2. Key Laboratory of Environmental Change and Natural Disaster, Beijing Normal University, Beijing 100875, China 3. School of Mathematical Science, Beijing Normal University, Beijing 100875, China |
|
|
Abstract The present paper analyzed the characteristics of particle swarm optimization(PSO), hybrid particle swarm optimization (HPSO) and fuzzy C-means (FCM), imported FCM into HPSO, and improved the HPSO-FCM arithmetic. An HPSO-FCM program was developed using Fortran language in MATLAB. Besides, a synthesis image combined with the former three principal components was obtained through band stacking and principal component analysis, taking the multispectral visible image of HJ-1 Satellite shot in June 2009 and the ASAR radar image of ENVISAT as basic data. And the paper has done a wetlands classification experiment in the synthesis image of the East Dongting Lake of Hunan province, using HPSO-FCM arithmetic and ISODATA separately. The results indicated: (1) The arithmetic which imported crossover operator of genetic algorithms and FCM into HPSO had better search speed and convergent precision, and it could search and optimize the best cluster center more efficiently. (2) The HPSO-FCM arithmetic has better precision in wetlands classification in multispectral remote sensing image, and it is an effective method in remote sensing image classification.
|
Received: 2010-05-10
Accepted: 2010-08-20
|
|
Corresponding Authors:
TANG Hong
E-mail: tanghong@bnu.edu.cn
|
|
[1] Paul A Keddy. Wetland Ecology Printiples and Consercation. Cambridge: Cambridge University Press, 2000. 124. [2] Holland M M. Wetlands and Environment Gradients. In: M ulamoottil G, W arner B G, McBean E A. Wetland Environment Gradients, Boundaries and Buffers. CRC Press Inc. 1996. 112. [3] Johnson R M, Barson M M. Australian Journal of Marine and Freshwater Research, 1993, 44(2): 235. [4] Wright C, Gallant A. Remote Sensing of Environment, 2007, 107(4): 582. [5] Li Xue, Jiang Weiguo, Sheng Shaoxue, et al. Research on Wetland Classification Approaches Based on Hyperion Hyperspectral Image. Proceedings of SPIE, 2009, 7498, 74981O. 1. [6] Eberhart R C, Kenedy J A. Particle Swarm Optimization. In: Proceedings of IEEE International Conference on Neural Networks, Perth, Australia, 1995. 1942. [7] Dunn J C. Cybernetics and Systems, 1973, (3): 32. [8] Bezdek J C. Pattern Recognition with Fuzzy Objective Function Algorithms. New York: Plenum, 1981. [9] CHEN Xi, LI Chun-yue, LI Feng, et al(陈 曦, 李春月, 李 峰, 等). Computer Engineering and Application(计算机工程与应用), 2008, 44(18): 181. [10] CHEN Rong-yuan, ZHANG Fei-yan, ZHANG Bin, et al(陈荣元, 张飞艳, 张 斌, 等). Journal of Electronics & Information Technology(电子与信息学报), 2009, 31(10): 2509. [11] ZHANG Lei, GAO Shang(张 磊, 高 尚). Computer Application and Seftware(计算机应用与软件), 2009, 26(12):89. [12] JI Zhen, LIAO Hui-lian, WU Qin-hua(纪 震, 廖惠连, 吴青华). The Application and Algorithm of Particle Swarm Optimization(粒子群算法及应用). Beijing: Science Press(北京: 科学出版社), 2009. [13] Angeline P. Using Selection to Improve Particle Swarm Optimization. In: Proceedings of IEEE Intl.Conf. on Evolutionary Computation(ICEC’98), Anchorage, 1998. 84. [14] Lovbjerg M. Rasmussen.Hybrid Particle Swarm Optimization with Breeding and Subpopulations. In: Proceedings of the third Genetic and Evolutionary Computation Conference, 2001. 56. [15] DUN Xiao-dong, WANG Cun-rui, LIU Xiang-dong(段晓东, 王存睿, 刘向东). The Application of Particle Swarm Optimization(粒子群算法及应用). Liaoning: Liaoning University Press(辽宁: 辽宁大学出版社), 2007. [16] YANG Kai, JIANG Hua-wei(杨 凯, 蒋华伟). Computer Engineering and Application(计算机工程与应用), 2009, 45(33): 179.
|
[1] |
LIANG Ye-heng1, DENG Ru-ru1, 2*, LIANG Yu-jie1, LIU Yong-ming3, WU Yi4, YUAN Yu-heng5, AI Xian-jun6. Spectral Characteristics of Sediment Reflectance Under the Background of Heavy Metal Polluted Water and Analysis of Its Contribution to
Water-Leaving Reflectance[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 111-117. |
[2] |
LI Hu1, ZHONG Yun1, 2, FENG Ya-ting1, LIN Zhen1, ZHU Shi-jiang1, 2*. Multi-Vegetation Index Soil Moisture Inversion Model Based on UAV
Remote Sensing[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 207-214. |
[3] |
ZHU Wen-jing1, 2,FENG Zhan-kang1, 2,DAI Shi-yuan1, 2,ZHANG Ping-ping3,JI Wen4,WANG Ai-chen1, 2,WEI Xin-hua1, 2*. Multi-Feature Fusion Detection of Wheat Lodging Information Based on UAV Multispectral Images[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 197-206. |
[4] |
LIANG Shou-zhen1, SUI Xue-yan1, WANG Meng1, WANG Fei1, HAN Dong-rui1, WANG Guo-liang1, LI Hong-zhong2, MA Wan-dong3. The Influence of Anthocyanin on Plant Optical Properties and Remote Sensing Estimation at the Scale of Leaf[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 275-282. |
[5] |
HUANG You-ju1, TIAN Yi-chao2, 3*, ZHANG Qiang2, TAO Jin2, ZHANG Ya-li2, YANG Yong-wei2, LIN Jun-liang2. Estimation of Aboveground Biomass of Mangroves in Maowei Sea of Beibu Gulf Based on ZY-1-02D Satellite Hyperspectral Data[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3906-3915. |
[6] |
LI Si-yuan, JIAO Jian-nan, WANG Chi*. Specular Reflection Removal Method Based on Polarization Spectrum
Fusion and Its Application in Vegetation Health Monitoring[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3607-3614. |
[7] |
ZHU Zhi-cheng1, WU Yong-feng2*, MA Jun-cheng2, JI Lin2, LIU Bin-hui3*, JIN Hai-liang1*. Response of Winter Wheat Canopy Spectra to Chlorophyll Changes Under Water Stress Based on Unmanned Aerial Vehicle Remote Sensing[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3524-3534. |
[8] |
CUI Zhen-zhen1, 2, MA Chao1, ZHANG Hao2*, ZHANG Hong-wei3, LIANG Hu-jun3, QIU Wen2. Absolute Radiometric Calibration of Aerial Multispectral Camera Based on Multi-Scale Tarps[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3571-3581. |
[9] |
TAO Jing-zhe1, 3, SONG De-rui1, 3, SONG Chuan-ming2, WANG Xiang-hai1, 2*. Multi-Band Remote Sensing Image Sharpening: A Survey[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 2999-3008. |
[10] |
FU Xiao-man1, 2, BAO Yu-long1, 2*, Bayaer Tubuxin1, 2, JIN Eerdemutu1, 2, BAO Yu-hai1, 2. Spectral Characteristics Analysis of Desert Steppe Vegetation Based on Field Online Multi-Angle Spectrometer[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3170-3179. |
[11] |
CHEN Hao1, 2, WANG Hao3*, HAN Wei3, GU Song-yan4, ZHANG Peng4, KANG Zhi-ming1. Impact Analysis of Microwave Real Spectral Response on Rapid Radiance Simulation[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3260-3265. |
[12] |
WANG Lin, WANG Xiang*, ZHOU Chao, WANG Xin-xin, MENG Qing-hui, CHEN Yan-long. Remote Sensing Quantitative Retrieval of Chlorophyll a and Trophic Level Index in Main Seagoing Rivers of Lianyungang[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3314-3320. |
[13] |
FENG Hai-kuan1, 2, YUE Ji-bo3, FAN Yi-guang2, YANG Gui-jun2, ZHAO Chun-jiang1, 2*. Estimation of Potato Above-Ground Biomass Based on VGC-AGB Model and Hyperspectral Remote Sensing[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2876-2884. |
[14] |
JIN Chun-bai1, YANG Guang1*, LU Shan2*, LIU Wen-jing1, LI De-jun1, ZHENG Nan1. Band Selection Method Based on Target Saliency Analysis in Spatial Domain[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2952-2959. |
[15] |
GAO Yu1, SUN Xue-jian1*, LI Guang-hua2, ZHANG Li-fu1, QU Liang2, ZHANG Dong-hui1, CHANG Jing-jing2, DAI Xiao-ai3. Study on the Derivation of Paper Viscosity Spectral Index Based on Spectral Information Expansion[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2960-2966. |
|
|
|
|