Sequential N-FINDR algorithms

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 7086, Issue , 2008, Pages

  Wu, Chao Cheng ^a   Chu, Shihyu ^a   Chang, Chein I ^a  

^a University of Marylandw Baltimore County   (United States)

Author keywords

Endmember extraction; Mixed pixels; Subpixel targets; Target Embeddedness (TE); Target Implantation (TI)

Indexed keywords

A-PRIORI; COMPUTATIONAL COSTS; ENDMEMBER EXTRACTION; ENDMEMBERS; EXHAUSTIVE SEARCH; IMAGING SPECTROMETRY; MIXED PIXELS; N-FINDR ALGORITHMS; PAPER ADDRESSES; PRACTICAL IMPLEMENTATION; RE-DESIGNING; SUBPIXEL TARGETS; TARGET EMBEDDEDNESS (TE); TARGET IMPLANTATION (TI); VIRTUAL DIMENSIONALITY;

ALGORITHMS; CHLORINE COMPOUNDS; MATHEMATICAL TECHNIQUES; SEQUENTIAL SWITCHING; SPECTROMETERS; SPECTROMETRY;

COMPUTATIONAL COMPLEXITY;

EID: 52349105056     PISSN: 0277786X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.795262     Document Type: Conference Paper

References (8)

1. M.E. Winter, "N-finder: an algorithm for fast autonomous spectral endmember determination in hyperspectral data," Image Spectrometry V, Proc. SPIE 3753, pp. 266-277, 1999.
2. J. W. Boardman, "Geometric mixture analysis of imaging spectrometery data," Proc. Int. Geoscience and Remote Sensing Symp., vol. 4, pp. 2369-2371, 1994.
3. F. Chaudhry, C. Wu, W. Liu, C.-I Chang and A. Plaza, Pixel Purity Index-Based Algorithms for Endemember Extraction from Hyperspectral Imagery, Chapter 3, Recent Advances in Hyperspectral Signal and Image Processing, edited by C.-I Chang, Trivandrum, Kerala: Research Signpost, India, 2006.
4. C.-I Chang and A. Plaza, "Fast iterative algorithm for implementation of pixel purity index," IEEE Geoscience and Remote Sensing Letters, vol. 3, no. 1, pp. 63-67, January 2006.
5. C.-I Chang, C. Wu, W. Liu and Y.C. Ouyang, "A growing method for simplex-based endmember extraction algorithms," IEEE Trans. on Geoscience and Remote Sensing, vol. 44, no. 10, pp. 2804-2819, October 2006.
6. C.-I Chang, Hyperspectral Imaging: Techniques for Spectral Detection and Classification, Kluwer Academic/Plenum Publishers, 2003.
7. C.-I Chang and Q. Du, "Estimation of number of spectrally distinct signal sources in hyperspectral imagery," IEEE Trans. on Geoscience and Remote Sensing, vol. 42, no. 3, pp. 608-619, March 2004.
8. J.C. Harsanyi and C.-I Chang, "Hyperspectral image classification and dimensionality reduction: an orthogonal subspace projection approach," IEEE Trans. Geosci. Remote Sensing, vol. 32, no. 4, pp. 779-785, July, 1994.