Dimensionality reduction based on clonal selection for hyperspectral imagery

IEEE Transactions on Geoscience and Remote Sensing

Volumn 45, Issue 12, 2007, Pages 4172-4186

  Zhang, Liangpei ^a,b   Zhong, Yanfei ^b   Huang, Bo ^c   Gong, Jianya ^b   Li, Pingxiang ^a,b  

^a IEEE   (China)

^b WUHAN UNIVERSITY   (China)

^c CHINESE UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

Artificial immune system (AIS); Artificial intelligence; Clonal selection; Dimensionality reduction; Feature selection; Remote sensing

Indexed keywords

ANTIGENIC STIMULUS; ARTIFICIAL IMMUNE SYSTEMS; CLONAL SELECTION; DIMENSIONALITY REDUCTION; STOCHASTIC SEARCH STRATEGIES;

ANTIBODIES; ARTIFICIAL INTELLIGENCE; FEATURE EXTRACTION; IMAGE RESOLUTION; IMMUNOLOGY; REMOTE SENSING;

IMAGE SENSORS;

EID: 36349016757     PISSN: 01962892     EISSN: None     Source Type: Journal    
DOI: 10.1109/TGRS.2007.905311     Document Type: Conference Paper

References (40)

1. C Lee and D. A. Landgrebe, "Analyzing high-dimensional multispectral data," IEEE Trans. Geosci. Remote Sens., vol. 31, no. 4, pp. 792-800, Jul. 1993.
2. K. Fukunaga, Introduction to Statistical Pattern Recognition, 2nd ed. New York: Academic, 1990.
3. C-I Chang and S. Wang, "Constrained band selection for hyperspectral imagery," IEEE Trans. Geosci. Remote Sens., vol. 44, no. 6, pp. 1575-1585, Jun. 2006.
4. A. Plaza, P. Martinez, J. Plaza, and R. Perez, "Dimensionality reduction and classification of hyperspectral image data using sequences of extended morphological transformations," IEEE Trans. Geosci, Remote Sens., vol. 43, no. 3, pp. 466-479, Mar. 2005.
5. G. F. Hughes, "On the mean accuracy of statistical pattern recognizers," IEEE Trans. Inf. Theory, vol. IT-14, no. 1, pp. 55-63, Jan. 1968.
6. A. R. Webb, Statistical Pattern Recognition, 2nd ed. Hoboken, NJ: Wiley, 2002.
7. A. Ifarraguerri and C-I Chang, "Unsupervised hyperspectral image analysis with projection pursuit," IEEE Trans. Geosci. Remote Sem., vol. 38, no. 6, pp. 2529-2538, Nov. 2000.
8. C Lee and D. A. Landgrebe, "Feature extraction based on decision boundaries," IEEE Trans. Pattern Anal Mack Intell., vol. 15, no. 4, pp. 388-400, Apr. 1993.
9. J. Wang and C.-I Chang, "Independent component analysis-based dimensionality reduction with applications in hyperspectral image analysis," IEEE Trans. Geosci. Remote Sem., vol. 44, no. 6, pp. 1586-1600, Jun. 2006.
10. C Lee and D. A. Landgrebe, "Decision boundary feature extraction for neural networks," IEEE Trans. Neural Netw., vol. 8, no. 1, pp. 75-83, Jan. 1997.
11. A. Jain and D. Zongker, "Feature selection: Evaluation, application, and small sample performance," IEEE Trans. Pattern Anal. Mech. Intell., vol. 19, no. 2, pp. 153-158, Feb. 1997.
12. L. Bruzzone, F. Roli, and S. B. Serpico, "An extension of the Jeffreys-Matusita distance to multiclass cases for feature selection," IEEE Trans. Geosci. Remote Sens., vol. 33, no. 6, pp. 1318-1321, Nov. 1995.
13. P. M. Narendra and K. Fukunaga, "A branch and bound algorithm for feature subset selection," IEEE Trans. Comput., vol. C-26, no. 9, pp. 917-922, Sep. 1977.
14. S.D. Stearns, "On selecting features for pattern classifiers," in Proc. 3rd Int. Conf. Pattern Recog., Coronado, CA, 1976, pp. 71-75.
15. P. Pudil, J. Novovicova, and J. Kittler, "Floating search methods in feature selection," Pattern Recognit Lett, vol. 15, no. 11, pp. 1119-1125, Nov. 1994.
16. W. Siedlecki and J. Sklansky, "A note on genetic algorithms for large scale feature selection," Pattern Recognit. Lett, vol. 10, no. 5, pp. 335-347, Nov. 1989.
17. M. Mitchell, An Introduction to Genetic Algorithms. Cambridge, MA: MIT Press, 1998. Reprint edition.
18. T. Mantere and J. T. Alander, "Evolutionary software engineering, a review," Appl. Soft Comput., vol. 5, no. 3, pp. 315-331, Mar. 2005.
19. M. L. Raymer, W. F. Punch, E. D. Goodman et al., "Dimensionality reduction using genetic algorithms,"IEEE Trans. Evol. Comput., vol. 4, no. 2, pp. 164-171, Jul. 2000.
20. W. Siedlecki and J. Sklansky, "On automatic feature selection," Int. J. Pattern Recognit. Artif. Intell., vol. 2, no. 2, pp. 197-220, 1988.
21. L. N. De Castro and F. J. Von Zuben, "Clonal selection algorithm with engineering applications," in Proc GECCO's, Las Vegas, NV, 2000, pp. 36-37.
22. L. N. De Castro and F. J. Von Zuben, "Learning and optimization using die clonal selection principle," IEEE Trans. Evol. Comput, vol. 6, no. 3, pp. 239-250, Jun. 2002.
23. D. Dasgupta, Artificial Immune Systems and Their Applications. Berlin, Germany: Springer-Verlag, 1999.
24. L. N. de Castro and J. Timmis, Artificial Immune Systems: A New Computational Intelligence Approach. London, U. K.: Springer-Verlag, 2002.
25. Y. Zhong, L. Zhang, B. Huang, and P. Li, "An unsupervised artificial immune classifier for multi/hyperspectral remote sensing imagery," IEEE Trans. Geosci. Remote Sens., vol. 44, no. 2, pp. 420-431, Feb. 2006.
26. F. M. Burnet, The Clonal Selection Theory of Acquired Immunity. Cambridge, U. K.: Cambridge Univ. Press, 1959.
27. F. M. Burnet, "Clonal selection and after," in Theoretical Immunology, G. I. Bell, A. S. Perelson, and G. H. Pimbley, Eds. New York: Marcel Dekker, 1978, pp. 63-85.
28. Y. Zhong, L. Zhang, J. Gong, and P. Li, "Classification of multi-spectral remote sensing image based on clonal selection," J. Image Graph., vol. 10, no. 1, pp. 18-24, 2005. (in Chinese).
29. N. K. Jerne, "The immune system," Sci. Amer., vol. 229, no. 1, pp. 52-60, 1973.
30. A. S. Perelsen and G. F. Oster, "Theoretical studies of clonal selection: Minimal antibody repertoire size and reliability of self-nonself discrimination," J. Theor. Biol., vol. 81, pp. 645-670, 1979.
31. L. Segel and A. S. Perelson, "Computations in shape space: A new approach to immune network theory," in Theoretical Immunology, A. S. Perelson, Ed. Reading, MA: Addison-Wesley, 1988, pp. 321-343. Part Two.
32. A. S. Perelson and G. Weisbuch, "Immunology for physicists," Rev. Mod. Phys., vol. 69, no. 4, pp. 1219-1267, 1997.
33. A. S. Perelson, "Immune network theory," Immunol. Rev., vol. 110, pp. 5-36, 1989.
34. L. N. De Castro and F. J. Von zuben, "Artificial immune systems: Part I - Basic theory and application," State Univ. Campinas, Campinas, Brazil, Tech. Rep.-RT DCA 0.1/99, 1999.
35. J. S. Chun, H. K. Jung, and S. Y. Hahn, "A study on comparison of optimization performances between immune algorithm and other heuristic algorithms," IEEE Trans. Magn., vol. 34, no. 5, pp. 2972-2975, Sep. 1998.
36. P. H. Swain and S. M. Davis, Remote Sensing: The Quantitative Approach. New York: McGraw-Hill, 1978.
37. L. Bruzzone and S. B. Serpico, "A technique for feature selection in multiclass problems," Int. J. Remote Sens., vol. 21, no. 3, pp. 549-563, Feb. 2000.
38. J. A. Richards, An Introduction to Remote Sensing Digital Image Analysis. Berlin, Germany: Springer-Verlag, 1986.
39. P. F. Hsieh and D. Landgrebe, "Classification of high dimensional data," Ph.D. dissertation, School Elect. Comput. Eng., Purdue Univ., West Lafayette, IN, 1998.
40. S. B. Serpico and L. Bruzzone, "A new search algorithm for feature selection in hyperspectral remote sensing images," IEEE Trans. Geosci. Remote Sens., vol. 39, no. 7, pp. 1360-1367, Jul. 2001.