Band selection based Gaussian processes for hyperspectral remote sensing images classification

Proceedings - International Conference on Image Processing, ICIP

Volumn , Issue , 2009, Pages 2845-2848

  Yao, Futian ^a   Qian, Yuntao ^a  

^a ZHEJIANG UNIVERSITY   (China)

Author keywords

Band selection; Classification; Gaussian process; Hyperspectral images; Remote sensing

Indexed keywords

COST REDUCTION; GAUSSIAN DISTRIBUTION; GAUSSIAN NOISE (ELECTRONIC); IMAGE RECONSTRUCTION; IMAGING SYSTEMS;

BAND SELECTION; BAYESIAN; CLASSIFICATION ACCURACY; COMPUTATIONAL COSTS; GAUSSIAN PROCESS; GAUSSIAN PROCESSES; HIGH DIMENSIONS; HYPER-SPECTRAL IMAGES; HYPERSPECTRAL REMOTE SENSING IMAGE; KNOWLEDGE DISCOVERY; MIXED PIXEL; NON-LINEAR METHODS; NONLINEAR DATA; NONLINEAR PROPERTIES; RESEARCH DIRECTIONS;

REMOTE SENSING;

EID: 77951956144     PISSN: 15224880     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICIP.2009.5414494     Document Type: Conference Paper

References (8)

1. G. Hughes, "On the mean accuracy of statistical pattern recognizers," Information Theory, IEEE Transactions on, vol. 14, no. 1, pp. 55-63, Jan 1968.
2. F. Melgani and L. Bruzzone, "Classification of hyperspectral remote sensing images with support vector machines," Geoscience and Remote Sensing, IEEE Transactions on, vol. 42, no. 8, pp. 1778-1790, Aug. 2004.
3. Y. Bazi and F. Melgani, "Toward an optimal svm classification system for hyperspectral remote sensing images," Geoscience and Remote Sensing, IEEE Transactions on, vol. 44, no. 11, pp. 3374-3385, Nov. 2006.
4. B.J. Frey and D. Dueck, "Mixture modeling by affinity propagation," in Neural Information Processing Systems., 2006, pp. 379-386.
5. Sen Jia, Yuntao Qian, and Zhen Ji, "Band selection for hyperspectral imagery using affinity propagation," Computing: Techniques and Applications, 2008. DICTA '08.Digital Image, pp. 137-141, Dec. 2008.
6. Carl Edward Rasmussen and Christopher K. I.Williams, Gaussian Processes for Machine Learning, The MIT press, 2006.
7. David Barber and Christopher K. I. Williams, "Gaussian processes for bayesian classification via hybrid monte carlo," in Advances in Neural Information Processing Systems 9. 1997, pp. 340-346, MIT Press.
8. Neil D. Lawrence, "Gaussian process latent variable models for visualisation of high dimensional data," in In NIPS, 2004.