Comparison of approaches for determining end-members in hyperspectral data

IEEE Aerospace Conference Proceedings

Volumn 3, Issue , 2000, Pages 305-313

  Winter, Michael E ^a   Winter, Edwin M ^b  

^a UNIVERSITY OF QUEENSLAND   (Australia)

^b Technical Research Associates Inc   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; ERROR ANALYSIS; IMAGE ANALYSIS; ITERATIVE METHODS; MATHEMATICAL MODELS; SPACECRAFT INSTRUMENTS;

AUTONOMOUS ALGORITHM; AUTONOMOUS METHODS; ENDMEMBER SPECTRA; HYPERSPECTRAL DATA; ITERATIVE ERROR ANALYSIS;

IMAGE SENSORS;

EID: 0034432355     PISSN: 1095323X     EISSN: None     Source Type: Journal    
DOI: 10.1109/AERO.2000.879860     Document Type: Article

References (12)

1. Minimum volume transforms for remotely sensed data
2. Automating spectral unmixing of AVIRIS data using convex geometry concepts
3. Use of filter vectors in hyperspectral data analysis
4. Fast autonomous spectral end-member determination in hyperspectral data
5. Automated endmembers selection: Part I theory
6. Comparison of SEM and linear unmixing approaches for classification of spectral data
7. Analysis, understanding and visualization of hyperspectral data as convex sets in n-space
8. Comparison of output from orasis and pixel purity calculations
9. Automatic endmember extraction from hyperspectral data for mineral exploration
10. The airborne visible/infrared imaging spectrometer (AVIRIS)
11. The U. S. geological survey, digital spectral library: Version 1:0.2 to 3.0 microns
12. Evolution in imaging spectroscopy analysis and sensor signal-to-noise: An examination of how far we have come