Spatial resolution enhancement of hyperspectral images using unmixing and binary particle swarm optimization

IEEE Geoscience and Remote Sensing Letters

Volumn 11, Issue 12, 2014, Pages 2100-2104

  Erturk, Alp ^a   Gullu, Mehmet Kemal ^a   Cesmeci, Davut ^a   Gercek, Deniz ^a   Erturk, Sarp ^a  

^a KOCAELI UNIVERSITY   (Turkey)

Author keywords

[No Author keywords available]

Indexed keywords

FIELD PROGRAMMABLE GATE ARRAYS (FPGA); IMAGE FUSION; INDEPENDENT COMPONENT ANALYSIS; LEAST SQUARES APPROXIMATIONS; PARTICLE SWARM OPTIMIZATION (PSO); SPECTRAL RESOLUTION; SPECTROSCOPY;

BINARY PARTICLE SWARM OPTIMIZATION; FULLY CONSTRAINED LEAST SQUARES (FCLS); HIGH SPECTRAL RESOLUTION; HYPER-SPECTRAL IMAGES; MULTISENSOR IMAGE FUSION; SATELLITE-TO-GROUND TRANSMISSION; SPATIAL REGULARIZATIONS; SPATIAL-RESOLUTION ENHANCEMENT;

IMAGE RESOLUTION;

EID: 84903535657     PISSN: 1545598X     EISSN: None     Source Type: Journal    
DOI: 10.1109/LGRS.2014.2320135     Document Type: Article

References (13)

1. D. A. Landgrebe, Signal Theory Methods in Multispectral Remote Sensing. New York, NY, USA: Wiley, 2003.
2. J. M. Bioucas-Dias et al., "Hyperspectral unmixing overview: Geometrical, statistical, sparse regression-based approaches, " IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens., vol. 5, no. 2, pp. 354-379, Apr. 2012.
3. N. Keshava and J. F. Mustard, "Spectral unmixing, " IEEE Signal Process. Mag., vol. 19, no. 1, pp. 44-57, Jan. 2002. (Pubitemid 34237207)
4. A. J. Tatem, H. G. Lewis, P. M. Atkinson, and M. S. Nixon, "Super-resolution target identification from remotely sensed images using a Hopfield neural network, " IEEE Trans. Geosci. Remote Sens., vol. 39, no. 4, pp. 781-796, Apr. 2001. (Pubitemid 32432734)
5. A. Villa, J. Chanussot, J. A. Benediktsson, M. Ulfarsson, and C. Jutten, "Super-resolution: An efficient method to improve spatial resolution of hyperspectral images, " in Proc. IEEE IGARSS, 2011, pp. 2003-2006.
6. A. Villa, J. Chanussot, J. A. Benediktsson, and C. Jutten, "Spectral unmixing for the classification of hyperspectral images at a finer resolution, " IEEE J. Sel. Topics Signal Process., vol. 5, no. 3, pp. 521-533, Jun. 2011.
7. A. Villa, J. Chanussot, J. A. Benediktsson, C. Jutten, and R. Dambreville, "Unsupervised methods for the classification of hyperspectral images with low spatial resolution, " Pattern Recognit., vol. 46, no. 6, pp. 1556-1568, Jun. 2013.
8. D. C. Heinz and C.-I Chang, "Fully constrained least squares linear spectral mixture analysis method for material quantification in hyperspectral imagery, " IEEE Trans. Geosci. Remote Sens., vol. 39, no. 3, pp. 529-545, Mar. 2001. (Pubitemid 32400422)
9. J. Kennedy and R. Eberhart, "Particle swarm optimization, " in Proc. IEEE Int. Conf. Neural Netw., 1995, vol. 4, pp. 1942-1948.
10. J. Kennedy and R. C. Eberhart, "A discrete binary version of the particle swarm optimization, " in Proc. IEEE Int. Conf. Syst., Man, Cybern., 1997, vol. 5, pp. 4104-4108.
11. F. Afshinmanesh, A. Marandi, and A. Rahimi-Khan, "A novel binary particle swarm optimization method using artificial immune system, " in Proc. Int. Conf. Comput. Tool EUROCON, 2005, vol. 1, pp. 217-220. (Pubitemid 46389005)
12. C.-I Chang and Q. Du, "Estimation of number of spectrally distinct signal sources in hyperspectral imagery, " IEEE Trans. Geosci. Remote Sens., vol. 42, no. 3, pp. 608-619, Mar. 2004.
13. J. M. P. Nascimento and J. M. Bioucas-Dias, "Vertex component analysis: A fast algorithm to unmix hyperspectral data, " IEEE Trans. Geosci. Remote Sens., vol. 43, no. 4, pp. 898-910, Apr. 2005. (Pubitemid 40476033).