TY  - GEN
AU  - Chang,Chein-I
TI  - Hyperspectral imaging: techniques for spectral detection and classification 
SN  - 0306474832
AV  - G70.4 .C46 2003
PY  - 2003///
CY  - New York
PB  - Kluwer Academic/Plenum Publishers
KW  - Image processing
KW  - Digital techniques
KW  - Görüntü işleme
KW  - Dijital teknikler
KW  - Remote sensing
KW  - Uzaktan algılama
N1  - Includes bibliographical references and index; 1. Introduction. Part I: Hyperspectral Measures. 2. Hyperspectral measures for spectral characterization. Part II: Subpixel Detection. 3. Target abundance-constrained subpixel detection. 4. Target signature-constrained subpixel detection: linearly constrained minimum variance (LCMV). 5. Automatic subpixel detection (unsupervised subpixel detection). 6. Anomaly detection. 7. Sensitivity of subpixel detection. Part III: Unconstrained Mixed Pixel Classification. 8. Unconstrained Mixed Pixel Classification: least squares subspace projection. 9. A quantitative analysis of mixed-to-pure pixel conversion. Part IV: Constrained Mixed Pixel Classification. 10. Target abundance-constrained mixed pixel classification (TACMPC). 11. Target signature-constrained mixed pixel classification (TSCMPC): LCMV multiple target classifiers. 12. Signature-constrained mixed pixel classification (TSCMPC): Linearly constrained discriminant analysis (LCDA). Part V: Automatic Mixed Pixel Classification (AMPC). 13. Automatic mixed pixel classification (AMPC): unsupervised mixed pixel classification. 14. Automatic mixed pixel classification (AMPC): anomaly classification. 15. Automatic mixed pixel classification (AMPC): linear spectral random mixture analysis (LSRMA). 16. Automatic mixed pixel classification (AMPC): projection pursuit. 17. Estimation of virtual dimensionality of hyperspectral imagery. 18. Conclusion and further techniques. Glossary. References. Index. )
ER  -