Solving adundance estimation in hyperspectral unmixing as a least distance problem

International Geoscience and Remote Sensing Symposium (IGARSS)

Volumn 5, Issue , 2004, Pages 3276-3278

  Vélez Reyes, Miguel ^a   Rosario, Samuel ^a  

^a UNIVERSITY OF PUERTO RICO   (Puerto Rico)

Author keywords

Hyperspectral imagery; Unmixing

Indexed keywords

ALGORITHMS; GAUSSIAN NOISE (ELECTRONIC); IMAGE ANALYSIS; IMAGE SENSORS; ITERATIVE METHODS; LEAST SQUARES APPROXIMATIONS; LIGHT REFLECTION; MATHEMATICAL MODELS; MATRIX ALGEBRA; PROBLEM SOLVING; VECTORS;

HYPERSPECTRAL IMAGERY; LINEAR MIXING MODEL (LMM); NONNEGATIVE LEAST SQUARE PROBLEMS (NNLS); UNMIXING;

REMOTE SENSING;

EID: 15944419508     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (5)

1. N. Keshava and J.F. Mustard. "Spectral unmixing." In IEEE Signal Processing Magazine, pp. 44-57, January 2002.
2. C.L. Lawson and R.J. Hanson, Solving Least Squares Problems, Prentice-Hall, 1974.
3. M. Velez-Reyes, S. Rosario, A. Puetz, R. B. Lockwood, "Iterative algorithms for unmixing of hyperspectral imagery." In Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery IX. Proceedings of SPIE Vol. 5093, April 2003.
4. Chang C. I.; Ren H.; et. al. "Subpixel Target Size Estimation for Remotely Sensed Imagery". In Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imogery IX, Proceedings of SPIE Vol. 5093, April 2003.
5. Rosario, S. Iterative Algorithms for Abundance Estimation on Unmixing of Hyperspectral Imagery. Master of Science Thesis. University of Puerto Rico at Mayagüez, May 2004.