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Volumn 9, Issue 9, 2009, Pages 7132-7149

Image-based airborne sensors: A combined approach for spectral signatures classification through deterministic simulated annealing

Author keywords

Bayesian classifier; Classifier combination; Deterministic simulated annealing; Fuzzy classifier; Image based airborne sensors; Spectral signatures classification; Unsupervised

Indexed keywords

AIR-BORNE SENSORS; BAYESIAN CLASSIFIER; CLASSIFIER COMBINATION; FUZZY CLASSIFIERS; SPECTRAL SIGNATURE; UNSUPERVISED;

EID: 70350033785     PISSN: 14248220     EISSN: None     Source Type: Journal    
DOI: 10.3390/s90907132     Document Type: Article
Times cited : (4)

References (40)
  • 1
    • 25144461009 scopus 로고    scopus 로고
    • Dynamic and static weighting in classifier fusion
    • Marques, J.S., Pérez de la Blanca, N., Pina, P., Eds.; Springer Berlin/Heidelberg: Berlin, Germany
    • Valdovinos, R.M.; Sánchez, J.S.; Barandela, R. Dynamic and static weighting in classifier fusion. In Pattern Recognition and Image Analysis, Lecture Notes in Computer Science; Marques, J.S., Pérez de la Blanca, N., Pina, P., Eds.; Springer Berlin/Heidelberg: Berlin, Germany, 2005; pp. 59-66.
    • (2005) Pattern Recognition and Image Analysis, Lecture Notes in Computer Science , pp. 59-66
    • Valdovinos, R.M.1    Sánchez, J.S.2    Barandela, R.3
  • 2
    • 33746817927 scopus 로고    scopus 로고
    • Automatic texture feature selection for image pixel classification
    • Puig, D.; García, M.A. Automatic texture feature selection for image pixel classification. Patt. Recog. 2006, 39, 1996-2009.
    • (2006) Patt. Recog , vol.39 , pp. 1996-2009
    • Puig, D.1    García, M.A.2
  • 4
    • 33845310027 scopus 로고    scopus 로고
    • Application of spectral features' ratios for improving classification in partially calibrated hyperspectral imagery: A case study of separating Mediterranean vegetation species
    • Rud, R.; Shoshany, M.; Alchanatis, V.; Cohen, Y. Application of spectral features' ratios for improving classification in partially calibrated hyperspectral imagery: a case study of separating Mediterranean vegetation species. J. Real-Time Image Process. 2006, 1, 143-152.
    • (2006) J. Real-Time Image Process. , vol.1 , pp. 143-152
    • Rud, R.1    Shoshany, M.2    Alchanatis, V.3    Cohen, Y.4
  • 5
    • 0035391738 scopus 로고    scopus 로고
    • Best-bases feature extraction for pairwise classification of hyperspectral data
    • Kumar, K.; Ghosh, J.; Crawford, M.M. Best-bases feature extraction for pairwise classification of hyperspectral data. IEEE Trans. Geosci. Remot. Sen. 2001, 39, 1368-1379.
    • (2001) IEEE Trans. Geosci. Remot. Sen , vol.39 , pp. 1368-1379
    • Kumar, K.1    Ghosh, J.2    Crawford, M.M.3
  • 7
    • 0037384819 scopus 로고    scopus 로고
    • Comparing texture analysis methods through classification
    • Maillard P. Comparing texture analysis methods through classification, Photogramm. Eng. Remote Sens. 2003, 69, 357-367.
    • (2003) Photogramm. Eng. Remote Sens , vol.69 , pp. 357-367
    • Maillard, P.1
  • 8
    • 0032663328 scopus 로고    scopus 로고
    • Filtering for texture classification: A comparative study
    • Randen, T.; Husøy, J.H. Filtering for texture classification: a comparative study. IEEE Trans. Patt. Anal. Mach. Int. 1999, 21, 291-310.
    • (1999) IEEE Trans. Patt. Anal. Mach. Int. , vol.21 , pp. 291-310
    • Randen, T.1    Husøy, J.H.2
  • 9
    • 33745941457 scopus 로고    scopus 로고
    • Texture Analysis. Signal Processing and Pattern Recognition
    • Jähne, B., Hauβecker, H., Geiβler, P., Eds.; Academic Press: St. Louis, MO, USA
    • Wagner, T. Texture Analysis. Signal Processing and Pattern Recognition. In Handbook of Computer Vision and Applications; Jähne, B., Hauβecker, H., Geiβler, P., Eds.; Academic Press: St. Louis, MO, USA, 1999.
    • (1999) Handbook of Computer Vision and Applications
    • Wagner, T.1
  • 10
    • 0031348906 scopus 로고    scopus 로고
    • Measuring texture classification algorithms. Patt. Recog
    • Smith, G.; Burns, I. Measuring texture classification algorithms. Patt. Recog. Lett. 1997, 18, 1495-1501.
    • (1997) Lett , vol.18 , pp. 1495-1501
    • Smith, G.1    Burns, I.2
  • 11
    • 0035425908 scopus 로고    scopus 로고
    • Experiments in colour texture analysis
    • Drimbarean, A.; Whelan, P.F. Experiments in colour texture analysis. Patt. Recog. Lett. 2003, 22, 1161-1167.
    • (2003) Patt. Recog. Lett , vol.22 , pp. 1161-1167
    • Drimbarean, A.1    Whelan, P.F.2
  • 13
    • 0346076780 scopus 로고    scopus 로고
    • Fuzzy vs non-fuzzy in combining classifiers designed by boosting
    • Kuncheva, L.I. Fuzzy vs non-fuzzy in combining classifiers designed by boosting. IEEE Trans. Fuzzy Syst. 2003, 11, 729-741.
    • (2003) IEEE Trans. Fuzzy Syst. , vol.11 , pp. 729-741
    • Kuncheva, L.I.1
  • 14
    • 0036080105 scopus 로고    scopus 로고
    • Hierarchical fusion of multiple classifiers for hyperspectral data analysis
    • Kumar, S.; Ghosh, J.; Crawford, M.M. Hierarchical fusion of multiple classifiers for hyperspectral data analysis. Patt. Anal. Appl. 2002, 5, 210-220.
    • (2002) Patt. Anal. Appl , vol.5 , pp. 210-220
    • Kumar, S.1    Ghosh, J.2    Crawford, M.M.3
  • 17
    • 0036086170 scopus 로고    scopus 로고
    • Multiple classifier systems: Software engineered, automatically modular leading to a taxonomic overview
    • Partridge, D.; Griffith, N. Multiple classifier systems: software engineered, automatically modular leading to a taxonomic overview. Patt. Anal. Appl. 2002, 5, 180-188.
    • (2002) Patt. Anal. Appl. , vol.5 , pp. 180-188
    • Partridge, D.1    Griffith, N.2
  • 18
    • 33646763167 scopus 로고    scopus 로고
    • Combining Multiple Precision-Boosted Classifiers for Indoor-Outdoor Scene Classification
    • Deng, D.; Zhang, J. Combining Multiple Precision-Boosted Classifiers for Indoor-Outdoor Scene Classification. Inform. Technol. Appl. 2005, 1, 720-725.
    • (2005) Inform. Technol. Appl , vol.1 , pp. 720-725
    • Deng, D.1    Zhang, J.2
  • 19
    • 0034875843 scopus 로고    scopus 로고
    • On combining classifiers using sum and product rules
    • Alexandre, L.A.; Campilho, A.C.; Kamel, M. On combining classifiers using sum and product rules. Patt. Recog. Lett. 2001, 22, 1283-1289.
    • (2001) Patt. Recog. Lett , vol.22 , pp. 1283-1289
    • Alexandre, L.A.1    Campilho, A.C.2    Kamel, M.3
  • 23
    • 0021518209 scopus 로고
    • Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images
    • Geman, S.; Geman, G. Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images. IEEE Trans. Patt. Anal. Mach. Int. 1984, 6, 721-741.
    • (1984) IEEE Trans. Patt. Anal. Mach. Int , vol.6 , pp. 721-741
    • Geman, S.1    Geman, G.2
  • 25
    • 0003771499 scopus 로고    scopus 로고
    • MIT Press: Cambridge, MA, USA
    • Palmer, S.E. Vision Science. MIT Press: Cambridge, MA, USA, 2004.
    • (2004) Vision Science
    • Palmer, S.E.1
  • 26
    • 77956465653 scopus 로고    scopus 로고
    • Encyclopedia of Artificial Intelligence
    • Rabuñal-Dopico, J. R., Dorado, J., Pazos A. Eds., IGI Global (IGI) publishing company: Hershey, PA, USA
    • Xu, L.; Amari, S.I. Encyclopedia of Artificial Intelligence. In Combining Classifiers and Learning Mixture-of-Experts; Rabuñal-Dopico, J. R., Dorado, J., Pazos A. Eds., IGI Global (IGI) publishing company: Hershey, PA, USA, 2008; pp. 318-326.
    • (2008) Combining Classifiers and Learning Mixture-of-Experts , pp. 318-326
    • Xu, L.1    Amari, S.I.2
  • 28
    • 70649101316 scopus 로고    scopus 로고
    • A hopfield neural network for combining classifiers applied to textured images
    • doi:10.1016/j.neunet.2009.07.019, in press
    • Pajares, G.; Guijarro, M.; Herrera, P.J.; Ribeiro, A. A hopfield neural network for combining classifiers applied to textured images. Neural Networks; doi:10.1016/j.neunet.2009.07.019, 2009, in press.
    • (2009) Neural Networks
    • Pajares, G.1    Guijarro, M.2    Herrera, P.J.3    Ribeiro, A.4
  • 31
    • 26444479778 scopus 로고
    • Optimization by simulated annealing
    • Kirkpatrick, S.; Gelatt, C.D.; Vecchi, M.P. Optimization by simulated annealing. Science 1983, 220, 671-680.
    • (1983) Science , vol.220 , pp. 671-680
    • Kirkpatrick, S.1    Gelatt, C.D.2    Vecchi, M.P.3
  • 32
    • 0343136966 scopus 로고
    • Optimization by simulated annealing: Quantitative studies
    • Kirkpatrick, S. Optimization by simulated annealing: quantitative studies. J. Statist. Phys. 1984, 34, 975-984.
    • (1984) J. Statist. Phys. , vol.34 , pp. 975-984
    • Kirkpatrick, S.1
  • 33
    • 0024012393 scopus 로고
    • Cooling schedules for optimal annealing
    • Hajek, B. Cooling schedules for optimal annealing. Math. Oper. Res. 1988, 13, 311-329.
    • (1988) Math. Oper. Res , vol.13 , pp. 311-329
    • Hajek, B.1
  • 35
    • 36948999941 scopus 로고    scopus 로고
    • University of California, School of Information and Computer Science: Irvine, CA, USA, (accessed September 7, 2009)
    • Asuncion, A.; Newman, D.J. UCI Machine Learning Repository. University of California, School of Information and Computer Science: Irvine, CA, USA; website http://archive.ics.uci.edu/ml/ (accessed September 7, 2009).
    • UCI Machine Learning Repository
    • Asuncion, A.1    Newman, D.J.2
  • 36
    • 33746791981 scopus 로고    scopus 로고
    • On the impact of fusion strategies on classification errors for large ensambles of classifiers
    • Cabrera, J.B.D. On the impact of fusion strategies on classification errors for large ensambles of classifiers. Patt. Recog. 2006, 39, 1963-1978.
    • (2006) Patt. Recog , vol.39 , pp. 1963-1978
    • Cabrera, J.B.D.1
  • 37
    • 0023855863 scopus 로고
    • On ordered weighted averaging aggregation operators in multicriteria decision making
    • Yager, R.R. On ordered weighted averaging aggregation operators in multicriteria decision making. IEEE Trans. Syst. Man Cybern. 1988, 18, 183-190.
    • (1988) IEEE Trans. Syst. Man Cybern , vol.18 , pp. 183-190
    • Yager, R.R.1
  • 38
    • 0033713738 scopus 로고    scopus 로고
    • Combining multiple classifiers by averaging or by multiplying?
    • Tax, D.M.J.; Breukelen, M.; Duin, R.P.W.; Kittler, J. Combining multiple classifiers by averaging or by multiplying? Patt. Recog. 2000, 33, 1475-1485.
    • (2000) Patt. Recog. , vol.33 , pp. 1475-1485
    • Tax, D.M.J.1    Breukelen, M.2    Duin, R.P.W.3    Kittler, J.4
  • 39
    • 0030837243 scopus 로고    scopus 로고
    • Adaptive color segmentation -A comparison of neural and statistical methods
    • Littmann, E.; Ritter, H. Adaptive color segmentation -A comparison of neural and statistical methods. IEEE Trans. Neural Networks 1997, 8, 175-185.
    • (1997) IEEE Trans. Neural Networks , vol.8 , pp. 175-185
    • Littmann, E.1    Ritter, H.2
  • 40
    • 0035546355 scopus 로고    scopus 로고
    • Color image segmentation: Advances and prospects
    • Cheng, H.D.; Jiang, X. H.; Sun, Y.; Wang, J. Color image segmentation: advances and prospects, Patt. Recog. 2001, 34, 2259-2281.
    • (2001) Patt. Recog. , vol.34 , pp. 2259-2281
    • Cheng, H.D.1    Jiang, X.H.2    Sun, Y.3    Wang, J.4


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