Hyperspectral remote sensing image classification based on support vector machine

Hongwai Yu Haomibo Xuebao/Journal of Infrared and Millimeter Waves

Volumn 27, Issue 2, 2008, Pages 123-128

  Tan, Kun ^a   Du, Pei Jun ^a  

^a CHINA UNIVERSITY OF MINING AND TECHNOLOGY   (China)

Author keywords

Classification; Hyperspectral remote sensing; Support vector machine (SVM)

Indexed keywords

NEURAL NETWORKS; REMOTE SENSING; SUPPORT VECTOR MACHINES;

HYPERSPECTRAL REMOTE SENSING; MINIMUM DISTANCE CLASSIFIER (MDC); OMIS SENSOR;

IMAGE CLASSIFICATION;

EID: 43849083251     PISSN: 10019014     EISSN: None     Source Type: Journal    
DOI: 10.3724/SP.J.1010.2008.00123     Document Type: Article

References (10)

1. Lothar Hermes, Dieter Frieau, Jan Puzicha, et al. Support Vector Machines for Land Usage Classification in Landsat TM Imagery[J]. In: Proc. IGARSS'99, 1: 348-350.
2. Huang C, Davis L S. Townshend J R G. An assessment of support vector machines for land cover classification[J]. International Journal of Remote Sensing, 2002, 23: 725-749.
3. Martin Brown, Hugh G Lewis, Steve R Gunn. Linear Spectral Mixture Models and Support Vector Machines for Remote Sensing[J]. IEEE Transactions on Geoscience and Remote Sensing, 2000, 38(5): 2346-2360.
4. DONG Guang-Jun, ZHANG Yong-Sheng, FAN Yong-Hong. Image fusion for hyperspectral data of PHI and high-resolution aerial image[J]. J. Infrared Millim. Waves, 2006, 25(2): 123-126.
5. Zhang J, Zhang Y, Zhou T. Classification of hyperspectral data using support vector machine[C]. In: IEEE International Conference on Image Processing, 2001: 882-885.
6. ZHANG Xue-Gong. Introduction statistical learning theory and support vector machines[J]. Act Automatica Sinica, 2000, 1(26): 32-42.
7. Vapnik V N. Statistical Learning Theory[M]. New York: Wiley. 1998.
8. Kreel U. Pairwise Classification and Support Vector Machines[M]. In Advances in Kernel Methods: Support Vector Learning, B. Scholkopf, C. J. C. Burges, and A. J. Smola (eds.), The MIT Press, Cambridge, MA, 1999: 255-268.
9. Hsu C W, Lin C J. A comparison of methods for multi-class support vector machines[J]. IEEE Transactions on Neural Networks, 2002, 13(2): 415-425, 2002.
10. Boardman J W, Kruse F A. Automated spectral analysis: a geological example using AVIRIS data, north Grapevine Mountains[C]. Nevada: In Proceeding, ERIM Tenth Thematic Conference on Geologic Remote Sensing, Environmental Research Institute of Michigan, Ann Arbor, MI, 1994, I-407-I-418.