Target detection in hyperspectral imagery based on linear mixing model reconstructed from measurements

Tien Tzu Hsueh Pao/Acta Electronica Sinica

Volumn 35, Issue 1, 2007, Pages 23-27

  He, Lin ^a   Pan, Quan ^a   Zhao, Yong Qiang ^a  

^a NORTHWESTERN POLYTECHNICAL UNIVERSITY   (China)

Author keywords

Hyperspectral imagery; Reconstructing from measurement; Spectral mixing model; Target detection

Indexed keywords

ALGORITHMS; IMAGING TECHNIQUES; INFRARED RADIATION; SPECTROGRAPHS; TARGET TRACKING;

BACKGROUND INTERFERENCE; DETECTION ALGORITHM; DETECTION POWER; HYPERSPECTRAL IMAGERY; MEASUREMENT RECONSTRUCTING; PEAK SIGNAL LOCAL CLUTTER MEAN RATIO (PSLCMR); SIGNAL LOCAL CLUTTER ROOT MEAN SQUARE ERROR (SLCR); SPECTRAL MIXING MODEL; SPECTRAL SUBSPACE; TARGET DETECTION; TARGET SPECTRAL;

SPECTRUM ANALYSIS;

EID: 34147194599     PISSN: 03722112     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (12)

1. H Ren, C I Chang. Automatic spectral target recognition in hyperspactral imagery[J]. IEEE Transactions on Aerospace Electronic. Systems, 2003, 39(4): 1232-1249.
2. J C Harsanyi, C I Chang. Hyperspectral image classification and dimensionality reductin: an orthogonal subspace projection approach[J]. IEEE Transactions on Geoscience and Remote Sensing, 1994, 32(7): 779-785.
3. C I Chang, S S Chiang. Anomaly detection and classification for hyperspectral imagery[J]. IEEE Transactions on Geoscience and Remote Sensing, 2002, 40(6): 1314-1325.
4. X Yu, I S Reed, A D Stacker. Comparative performance analysis of adaptive multispectral detectors[J]. IEEE Transactions on Signal Processing, 41(8), 1993: 2639-2656.
5. X Yu, L E Hoff, I S Reed, et al. Automatic target detection and recognition in multispectral imagery: A Unified ML Detection and Estimation Approach[J]. IEEE Transactions on Image Processing, 1997, 6(1): 143-156.
6. C Brumbley, C-I Chang. An unsupervised vector quantization-based target subspace projection approach to mixed pixel detection and classification in unknown background for remotely sensed imagery[J]. Pattern recognition, 1999, 32(7): 1161-1174.
7. T M Tu, C H Chen, C I Chang. A posteriori least squares orthogonal subspace projection approach to desired signature[J]. IEEE Transactions on Geoscience and Remote Sensing, 1997, 35(1): 127-139.
8. A Ifarraguerri, C I Chang. Multispectral and hyperspectral image analysis with convex cones[J]. IEEE Transactions on Geoscience and Remote Sensing, 1999, 37(2): 756-770.
9. H Ren, C I Chang. A generalized orthogonal subspace projection approach to unsupervised multispectral image classification[J]. IEEE Transactions on Geoscience and Remote Sensing, 2000, 38(6): 2515-2528.
10. S Haykin. Adaptive Filter Theory[M]. New Jersey: Prentice Hall, 2002.
11. L L Scharf. Statistical Signal Processing: Detection, Estimation, and Time Series Analysis[M]. New York: Addison-Wesley, 1991: 377-381.
12. N Keshava, J F Mustard. Spectral Unmixing[J]. IEEE Signal Processing Magazine, 2002, 19(1): 44-57.