A study between orthogonal subspace projection and generalized likelihood ratio test in hyperspectral image analysis

International Geoscience and Remote Sensing Symposium (IGARSS)

Volumn 5, Issue , 2002, Pages 2575-2577

  Du, Qian ^a   Ren, Hsuan ^a   Chang, Chein I ^a  

^a TEXAS A AND M UNIVERSITY KINGSVILLE   (United States)

Author keywords

Classification; Detection; Generalized likelihood ratio test; Hyperspectral imagery; Orthogonal subspace projection

Indexed keywords

COMPUTER SIMULATION; GAUSSIAN NOISE (ELECTRONIC); INFRARED SPECTROMETERS; MATHEMATICAL MODELS; MATRIX ALGEBRA; MAXIMUM LIKELIHOOD ESTIMATION; PROBABILITY DENSITY FUNCTION; PROJECTION SYSTEMS; SIGNAL DETECTION; SIGNAL TO NOISE RATIO; WHITE NOISE;

BINARY HYPOTHESIS TESTING PROBLEM; GENERALIZED LIKELIHOOD RATIO TEST; HYPERSPECTRAL IMAGE ANALYSIS; ORTHOGONAL SUBSPACE PROJECTION; WHITE GAUSSIAN NOISE;

IMAGE ANALYSIS;

EID: 0036402724     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (3)

1. J. C. Harsanyi and C.-I Chang, "Hyperspectral image classification and dimensionality reduction: an orthogonal subspace projection," IEEE Trans. Geoscience and Remote Sensing, vol. 32, pp. 4, pp. 779-785, 1994.
2. L. Scharf and B. Friedlander, "Matched subspace detector," IEEE Trans. Signal Processing, vol. 42, no. 8, pp. 2146-2157, 1994.
3. H. Ren and C.-I Chang, "A generalized orthogonal subspace projection approach to unsupervised multispectral image classification," IEEE Trans. Geoscience and Remote Sensing, vol. 38, no. 6, pp. 2515-2528, November 2000.