Unsupervised classification of remotely sensed images using Gaussian mixture models and particle swarm optimization

International Geoscience and Remote Sensing Symposium (IGARSS)

Volumn , Issue , 2010, Pages 1859-1862

  Ari, Çaǧlar ^a   Aksoy, Selim ^a  

^a BILKENT UNIVERSITY   (Turkey)

Author keywords

Clustering; Covariance parametrization; Gaussian mixture models; Maximum likelihood estimation; Particle swarm optimization; Stochastic search

Indexed keywords

COVARIANCE MATRIX; GAUSSIAN DISTRIBUTION; IMAGE CLASSIFICATION; ITERATIVE METHODS; MAXIMUM LIKELIHOOD ESTIMATION; MAXIMUM PRINCIPLE; PARTICLE SWARM OPTIMIZATION (PSO); REMOTE SENSING; SPECTROSCOPY; STOCHASTIC MODELS; STOCHASTIC SYSTEMS;

CLUSTERING; GAUSSIAN MIXTURE MODEL; OPTIMIZATION FORMULATIONS; PARAMETRIZATIONS; POPULATION-BASED ALGORITHM; STOCHASTIC SEARCH; STOCHASTIC SEARCH ALGORITHMS; UNSUPERVISED CLASSIFICATION;

CLUSTERING ALGORITHMS;

EID: 78650924032     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IGARSS.2010.5653855     Document Type: Conference Paper

References (5)

1. D.-X. Chang, X.-D. Zhang, and C.-W. Zheng, "A genetic algorithm with gene rearrangement for k-means clustering," Pattern Recognition, vol. 42, no. 7, pp. 1210-1222, July 2009.
2. U. Maulik and I. Saha, "Modified differential evolution based fuzzy clustering for pixel classification in remote sensing imagery," Pattern Recognition, vol. 42, no. 9, pp. 2135-2149, September 2009.
3. A. Paoli, F. Melgani, and E. Pasolli, "Clustering of hyper-spectral images based on multiobjective particle swarm optimization," IEEE TGARS, vol. 47, no. 12, pp. 4175-4188, December 2009.
4. G. H. Golub and C. F. Van Loan, Matrix Computations, Johns Hopkins University Press, 3rd edition, 1996.
5. J. Edmonds and R. M. Karp, "Theoretical improvements in algorithmic efficiency for network flow problems," Journal of the ACM, vol. 19, no. 2, pp. 248-264, April 1972.