Author Affiliations
1School of Electronic and Information Engineering, Liaoning Technical University, Huludao, Liaoning 125105, China2School of Electrical and Control Engineering, Liaoning Technical University, Huludao, Liaoning 125105, Chinashow less
Fig. 1. Linear mixed model of hyperspectral images
Fig. 2. Minimum-volume simplex
Fig. 3. Pseudo-code of MVSR-NMF algorithm
Fig. 4. Pseudo-code of abundance features calculated by ADMM
Fig. 5. Pseudo-code of endmember features calculated by ADMM
Fig. 6. Elementary abundance maps of synthetic data SYN1.(a) Endmember 1; (b) endmember 2; (c) endmember 3; (d) endmember 4; (e) endmember 5; (f) endmember 6
Fig. 7. Elementary abundance maps of synthetic data SYN2. (a) Endmember 1; (b) endmember 2; (c) endmember 3; (d) endmember 4; (e) endmember 5; (f) endmember 6
Fig. 8. Urban scene image
Fig. 9. Elementary abundance maps of synthetic data SYN1. (a) Original image; (b) FMVSA algorithm; (c) SISAL algorithm; (d) MVC-NMF algorithm; (e) CoNMF algorithm; (f) MVSR-NMF algorithm
Fig. 10. Elementary abundance maps of synthetic data SYN2. (a) Original image; (b) FMVSA algorithm; (c) SISAL algorithm; (d) MVC-NMF algorithm; (e) CoNMF algorithm; (f) MVSR-NMF algorithm
Fig. 11. Abundances of different algorithms. (a) Original image; (b) FMVSA algorithm; (c) SISAL algorithm; (d) MVC-NMF algorithm; (e) CoNMF algorithm; (f) MVSR-NMF algorithm
Fig. 12. Comparison of endmember spectral bands under different algorithms. (a) Original endmember spectral bands; (b) endmember spectral bands of MVC-NMF algorithm; (c) endmember spectral bands of CoNMF algorithm; (d) endmember spectral bands of MVSR-NMF algorithm
Algorithm | ESA /(°) | EFAA /(°) | t /s |
---|
20dB | 25dB | 30dB | 35dB | 40dB | 20dB | 25dB | 30dB | 35dB | 40dB |
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FMVSA | 6.69 | 4.63 | 2.61 | 1.63 | 1.03 | 22.93 | 16.28 | 9.34 | 5.52 | 3.19 | 21.55 | SISAL | 4.43 | 2.89 | 1.81 | 1.18 | 0.86 | 15.82 | 11.21 | 6.75 | 5.24 | 4.35 | 27.82 | MVC-NMF | 3.25 | 1.91 | 1.03 | 0.55 | 0.25 | 13.87 | 8.55 | 4.78 | 2.63 | 1.35 | 2159.97 | CoNMF | 1.93 | 1.46 | 1.02 | 0.51 | 0.28 | 12.47 | 7.97 | 5.22 | 3.28 | 1.96 | 127.22 | MVSR-NMF | 1.48 | 0.78 | 0.51 | 0.33 | 0.21 | 12.31 | 7.43 | 4.75 | 2.98 | 1.84 | 35.54 |
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Table 1. Performance comparison of endmember estimation and abundance estimation of synthetic data SYN1in different signal-to-noise ratios
Algorithm | ESA /(°) | EFAA /(°) | t /s |
---|
20dB | 25dB | 30dB | 35dB | 40dB | 20dB | 25dB | 30dB | 35dB | 40dB |
---|
FMVSA | 6.82 | 6.33 | 2.60 | 1.61 | 0.99 | 30.25 | 29.35 | 16.26 | 10.64 | 6.37 | 23.48 | SISAL | 3.27 | 2.04 | 1.55 | 0.93 | 0.67 | 24.79 | 17.69 | 11.53 | 7.32 | 4.25 | 33.41 | MVC-NMF | 2.85 | 1.73 | 1.01 | 0.53 | 0.24 | 22.89 | 16.41 | 10.24 | 5.77 | 2.81 | 2549.52 | CoNMF | 1.68 | 1.13 | 0.89 | 0.49 | 0.35 | 18.97 | 14.45 | 9.98 | 5.94 | 3.68 | 244.27 | MVSR-NMF | 1.39 | 0.96 | 0.64 | 0.40 | 0.23 | 17.78 | 12.13 | 10.51 | 5.39 | 3.64 | 55.49 |
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Table 2. Performance comparison of endmember estimation and abundance estimation of synthetic data SYN2 in different signal-to-noise ratios
Method | MVC-NMF | FMVSA | CoNMF | SISAL | MVSR-NMF |
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| 2.97 | 2.91 | 2.53 | 2.61 | 2.48 | | 1.04 | 0.87 | 0.83 | 0.96 | 0.81 |
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Table 3. Performance comparison of endmember matrix and abundance matrix in different algorithms