A maximum entropy approach to unsupervised mixed-pixel decomposition

IEEE Transactions on Image Processing

Volumn 16, Issue 4, 2007, Pages 1008-1021

  Miao, Lidan ^a   Qi, Hairong ^a   Szu, Harold ^b  

^a University of Tennessee   (United States)

^b The George Washington University   (United States)

Author keywords

Endmember; Hyperspectral data; Least squares; Maximum entropy; Mixed pixel decomposition; Spectral signature

Indexed keywords

ALGORITHMS; CHARACTER RECOGNITION; ERRORS; GEOMETRY; LEAST SQUARES APPROXIMATIONS; NUMERICAL METHODS; PIXELS; SPECTRUM ANALYSIS;

GRADIENT DESCENT MAXIMUM ENTROPY (GDME); HYPERSPECTRAL DATA; LEAST SQUARES ERROR; MIXED-PIXEL DECOMPOSITION; SPECTRAL SIGNATURE;

ELECTRONIC DOCUMENT IDENTIFICATION SYSTEMS;

ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; ENTROPY; EVALUATION; IMAGE ENHANCEMENT; INFORMATION RETRIEVAL; METHODOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING; STATISTICAL MODEL;

ALGORITHMS; COMPUTER SIMULATION; ENTROPY; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; INFORMATION STORAGE AND RETRIEVAL; MODELS, STATISTICAL; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 34047244201     PISSN: 10577149     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIP.2006.891350     Document Type: Article

References (42)

1. N. Keshava, "A survey of spectral unmixing algorithms," Lincoln Lab. J., vol. 14, no. 1, pp. 55-78, 2003.
2. J. J. Settle and N. A. Drake, "Linear mixing and the estimation of ground cover proportions," Int. J. Remote Sens., vol. 14, no. 6, pp. 1159-1177, 1993.
3. C. C. Borel and S. A. Gerstl, "Nonlinear spectral mixing models for vegetative and soils surface," Remote Sens. Environ., vol. 47, no. 2, pp. 403-416, 1994.
4. T. W. Ray and B. C. Murray, "Nonlinear spectral mixing in desert vegetation," Remote Sens. Environ., vol. 55, no. 1, pp. 59-64, Jan. 1996.
5. L. Zhang, D. Li, Q. Tong, and L. Zheng, "Study of the spectral mixture model of soil and vegetation in poyang lake area, China," Int. J. Remote Sens., vol. 19, no. 11, pp. 2077-2084, Jul. 1998.
6. K. J. Guilfoyle, M. L. Althouse, and C.-I. Chang, "A quantitative and comparative analysis of linear and nonlinear spectral mixture models using radial basis function neural network," IEEE Trans. Geosci. Remote Sens., vol. 39, no. 8, pp. 2314-2318, Aug. 2001.
7. C.-I. Chang and D. C. Heinz, "Constrained subpixel target detection for remotely sensed imagery," IEEE Trans. Geosci. Remote Sens., vol. 38, no. 3, pp. 1144-1159, May 2000.
8. M. O. Smith, P. E. Johnson, and J. B. Adams, "Quantitative determination of mineral types and abundances from reflectance spectral using principal components analysis," J. Geophys. Res., no. 90, pp. C797-C804, 1985.
9. R. A. Neville, K. Staenz, T. Szeredi, J. Lefebvre, and P. Hauff, "Automatic endmember extraction from hyperspectral data for mineral exploration, "in Proc. 21st Can. Symp. Remote Sensing, Ottawa, ON, Canada, 1999, vol. 2, pp. 891-896.
10. M. S. Gebbinck, "Decomposition of mixed pixels in remote sensing images to improve the area estimation of agricultural fields," Ph.D. dissertation, Univ. Nijmegen, Nijmegen, The Netherlands, 1998.
11. H. Tsurui, H. Nishimura, S. Hattori, S. Hirose, K. Okumura, and T. Shirai, "Seven-color fluorescence imaging of tissue samples based on fourier spectroscopy and singular value decomposition," J. Histochemi. Cytochem., vol. 48, no. 5, pp. 653-662, 2000.
12. M. E. Dickinson, G. Bearman, S. Tille, R. Lansford, and S. E. Fraser, "Multi-spectral imaging and linear unmixing add a whole new dimension to laser scanning fluorescence microscopy," BioImag., vol. 31, no. 6, pp. 1272-1278, 2001.
13. T. Zimmermann, J. Rietdorf, and R. Pepperkok, "Spectral imaging and its applications in live cell microscopy," Fed. Eur. Biochem. Soc., vol. 546, pp. 87-92, 2003.
14. R. H. Yuhas, A. F. H. Goetz, and J. W. Boardman, "Discrimination among semi-arid landscape endmembers using the spectral angle mapper (sam) algorithm," in Proc. Summaries 3rd Annu. JPL Airborne Geoscience Workshop, R. O. Green, Ed., 1992, vol. 1, pp. 147-149, JPL Publ. 92-14.
15. A. M. Cross, J. J. Settle, and N. A. D. R. T. M. Paivinen, "Subpixel measurement of tropical forest cover using avhrr data," Int. J. Remote Sens., vol. 12, no. 5, pp. 1119-1129, 1991.
16. G. Healcy and D. Slater, "Models and methods for automated material identification in hyperspectral imagery acquired under unknown illumination and atmospheric conditions," IEEE Trans. Geosci. Remote Sens., vol. 37, no. 6, pp. 2706-2717, Nov. 1999.
17. M. D. Craig, "Minimum-volume transforms for remotely sensed data," IEEE Trans. Geosci. Remote Sens., vol. 32, no. 3, pp. 542-552, May 1994.
18. J. W. Boardman, F. A. Kruse, and R. O. Green, "Mapping target signatures via partial unmixing of aviris data," in Proc. Summaries 5th Annu. JPL Airborne Earth Science Workshop, R. O. Green, Ed., 1995, vol. 1, pp. 23-26.
19. M. E. Winter, "N-findr: An algorithm for fast autonomous spectral end-member determination in hyperspectral data," in Proc. SPIE Conf. Imaging Spectrometry V, 1999, pp. 266-275.
20. J. M. P. Nascimento and J. M. B. 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.
21. J. J. Settle, "On the relationship between spectral unmixing and subspace projection," IEEE Trans. Geosci. Remote Sens., vol. 34, no. 4, pp. 1045-1046, Jul. 1996.
22. 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.
23. G. M. Foody, "Approaches for the production and evaluation of fuzzy land cover classifications from remotely-sensed data," Int. J. Remote Sens., vol. 17, pp. 1317-1340, 1996.
24. L. Bastin, "Comparison of fuzzy c-means classification, linear mixture modelling and mlc probabilities as tools for unmixing coarse pixels," Int. J. Remote Sens., vol. 18, no. 17, pp. 3629-3648, 1997.
25. G. M. Foody, "Thematic mapping from remotely sensed data with neural networks: MLP, RBF, and PNN based approaches," J. Geograph. Syst., vol. 3, pp. 217-232, 2001.
26. F. van der Meer, "Iterative spectral unmixing (isu)," Int. J. Remote Sens., vol. 20, no. 17, pp. 3431-3436, Nov. 1999.
27. J. Bayliss, J. A. Gualtieri, and R. Cromp, "Analyzing hyperspectral data with independent component analysis," Proc. SPIE, vol. 3240, pp. 133-143, 1997.
28. J. M. P. Nascimento and J. M. B. Dias, "Does independent component analysis play a role in unmixing hyperspectral data," IEEE Trans. Geosci. Remote Sens., vol. 43, no. 1, pp. 175-184, Jan. 2004.
29. C.-Y. Liou and K. O. Yang, "Unsupervised classification of remote sensing imagery with non-negative matrix factorization," presented at the Int. Conf. ONIP, 2005.
30. V. P. Paura, J. Piper, and R. J. Plemmons, "Nonnegative matrix factorization for spectral data analysis," Linear Algebra Applicat., to be published.
31. E. T. Jaynes, "Information theory and statistical mechanics," Rev. Modern Phys., vol. 27, pp. 620-630, 1957.
32. M. S. Gebbinck and T. E. Schoulen, J. Desachy, Ed., "Decomposition of mixed pixels," in Proc. Image and Signal Processing Remote Sensing II, 1995, vol. 2579, pp. 104-115.
33. S. Chettri and N. Netanyahu, "Spectral unmixing of remotely sensed imagery using maximum entropy," Proc. SPIE, vol. 2962, pp. 55-62, 1997.
34. M. P. Bertsekas, Constrained Optimization and Lagrange Multiplier Methods. New York: Academic, 1982.
35. B. Hapke, Theory of Reflectance and Emittance Spectroscopy. Cambridge, U.K.: Cambrige, 1993.
36. R. Bro and S. D. Jong, "A fast non-negativity constrained least squares algorithm," J. Chemom., vol. 11, pp. 393-401, 1997.
37. R. N. Clark, G. A. Swayze, A. Gallagher, T.V. King, and W. M. Calvin, "The u.s. geological survey digital spectral library: Version 1:0.2 to 3.0 μvm," Open File Rep. 93-592, U.S. Geol. Surv. 1993.
38. P. E. Johnson, "Simple algorithm for remote determination of mineral abundances and particle sizes from reflectance spectra," J. Geophys. Res., vol. 97, no. E2, pp. 2649-2657, Feb. 1992.
39. G. Swayze, R. Clark, S. Sutley, and A. Gallagher, "Ground-truthing aviris mineral mapping at cuprite, nevada," in Proc. Summaries 3rd Annu. JPL Airborne Geosciences Workshop, 1992, vol. 1, pp. 47-49.
40. F. A. Kruse, J. W. Boardman, and J. F. Huntington, "Comparison of airborne hyperspectral data and co-1 hyperion for mineral mapping," IEEE Trans. Geosci. Remote Sens., vol. 41, no. 6, pp. 1388-1400, Jun. 2003.
41. Swayze, "The hydrothermal and structural history of the cuprite mining district, southwestern Nevada: An integrated geological and geophysical approach," Ph.D. dissertation, Univ. Colorado, Boulder, 1997.
42. 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.