Author Affiliations
College of Air and Missile Defense, Air Force Engineering University, Xi'an, Shaanxi 710051, Chinashow less
Fig. 1. [in Chinese]
Fig. 2. Spectral imaging based on spatial compressive sampling and spectral KL transform
Fig. 3. SNR of each band of spectral image
Fig. 4. PSNR of each band of reconstructed spectral image for 2D-CRPG algorithm with different
Rspa
. (a)
K
=10; (b)
K
=150
Fig. 5. Two-dimensional image reconstruction effect of 2D-CRPG algorithm with different
Rspa
under condition of
K=
150
Fig. 6. PSNR of each band of reconstructed spectral image for 2D-CRPG algorithm with different
K
values. (a)
Rspa
=40%; (b)
Rspa
=90%
Fig. 7. PSNR of each band of reconstructed spectral image for different algorithms. (a)
Rspa
=40%; (b)
Rspa
=50%; (c)
Rspa
=60%; (d)
Rspa
=70%; (e)
Rspa
=80%; (f)
Rspa
=90%
Fig. 8. False color images of reconstructed spectral images for different algorithms with
Rspa
=40% (bands 250, 222, 10). (a) Original image; (b) BCS,
aAPSNR
=28.86 dB; (c) CSC,
aAPSNR
=27.08 dB; (d) 2D-OMP,
aAPSNR
=26.41 dB; (e) Kro-OMP,
aAPSNR
=19.05 dB; (f) 2D-CRPG,
aAPSNR
=33.14 dB
Fig. 9. False color images of reconstructed spectral images for different algorithms with
Rspa
=90% (bands 250, 222, 10). (a) Original image; (b) BCS,
aAPSNR
=34.54 dB; (c) CSC,
aAPSNR
=32.95 dB; (d) 2D-OMP,
aAPSNR
=35.41 dB; (e) Kro-OMP,
aAPSNR
=23.10 dB; (f) 2D-CRPG,
aAPSNR
=42.81 dB
Fig. 10. APSNR of different algorithms with different
Rspa