Figure 1.
General scheme of the proposed approach.
Figure 1.
General scheme of the proposed approach.
Figure 2.
Three examples of multi-temporal neighborhood areas: (a,b) the central changed pixels are located in the changed homogeneous areas; (c,d) the central changed pixels are located in the edge areas between two different changed areas; (e,f) the central changed pixels are located in the edge areas between the unchanged and changed areas.
Figure 2.
Three examples of multi-temporal neighborhood areas: (a,b) the central changed pixels are located in the changed homogeneous areas; (c,d) the central changed pixels are located in the edge areas between two different changed areas; (e,f) the central changed pixels are located in the edge areas between the unchanged and changed areas.
Figure 3.
Two examples of unchanged multi-temporal neighborhood areas: (a,b) the center pixels are located in the unchanged homogeneous areas; (c,d) the center pixels are located in the edge areas between two different unchanged areas.
Figure 3.
Two examples of unchanged multi-temporal neighborhood areas: (a,b) the center pixels are located in the unchanged homogeneous areas; (c,d) the center pixels are located in the edge areas between two different unchanged areas.
Figure 4.
AUC of STANR with from 0.1 to 0.9 in two data sets.
Figure 4.
AUC of STANR with from 0.1 to 0.9 in two data sets.
Figure 5.
Multi-temporal images in Peixian. (a) Image acquired in July 2008. (b) Image acquired in August 2009. (c) Reference map, where the changed pixels are shown in white and the unchanged pixels are shown in black.
Figure 5.
Multi-temporal images in Peixian. (a) Image acquired in July 2008. (b) Image acquired in August 2009. (c) Reference map, where the changed pixels are shown in white and the unchanged pixels are shown in black.
Figure 6.
Multi-temporal images in Bern. (a) Image acquired in April 1999. (b) Image acquired in May 1999. (c) Reference map, where the changed pixels are shown in white and the unchanged pixels are shown in black.
Figure 6.
Multi-temporal images in Bern. (a) Image acquired in April 1999. (b) Image acquired in May 1999. (c) Reference map, where the changed pixels are shown in white and the unchanged pixels are shown in black.
Figure 7.
Difference images acquired from the Peixian data set by using (a) IR, (b) LR, (c) NLMR, (d) MR 3 × 3, (e) MR 5 × 5, (f) MR 7 × 7, (g) MR 9 × 9, (h) NR 3 × 3, (i) NR 5 × 5, (j) NR 7 × 7, (k) NR 9 × 9, (l) INR 3 × 3, (m) INR 5 × 5, (n) INR 7 × 7, (o) INR 9 × 9, (p) GLRT 3 × 3, (q) GLRT 5 × 5, (r) GLRT 7 × 7, (s) GLRT 9 × 9, and (t) STANR, = 5, = 11, = 0.5.
Figure 7.
Difference images acquired from the Peixian data set by using (a) IR, (b) LR, (c) NLMR, (d) MR 3 × 3, (e) MR 5 × 5, (f) MR 7 × 7, (g) MR 9 × 9, (h) NR 3 × 3, (i) NR 5 × 5, (j) NR 7 × 7, (k) NR 9 × 9, (l) INR 3 × 3, (m) INR 5 × 5, (n) INR 7 × 7, (o) INR 9 × 9, (p) GLRT 3 × 3, (q) GLRT 5 × 5, (r) GLRT 7 × 7, (s) GLRT 9 × 9, and (t) STANR, = 5, = 11, = 0.5.
Figure 8.
Change maps acquired from the Peixian data set by using (a) IR, (b) LR, (c) NLMR, (d) MR 7 × 7, (e) NR 7 × 7, (f) INR 7 × 7, (g) GLRT 7 × 7, and (h) STANR, = 5, = 11, = 0.5.
Figure 8.
Change maps acquired from the Peixian data set by using (a) IR, (b) LR, (c) NLMR, (d) MR 7 × 7, (e) NR 7 × 7, (f) INR 7 × 7, (g) GLRT 7 × 7, and (h) STANR, = 5, = 11, = 0.5.
Figure 9.
Difference images acquired from the Bern data set by using (a) IR, (b) LR, (c) NLMR, (d) MR 3 × 3, (e) MR 5 × 5, (f) MR 7 × 7, (g) MR 9 × 9, (h) NR 3 × 3, (i) NR 5 × 5, (j) NR 7 × 7, (k) NR 9 × 9, (l) INR 3 × 3, (m) INR 5 × 5, (n) INR 7 × 7, (o) INR 9 × 9, (p) GLRT 3 × 3, (q) GLRT 5 × 5, (r) GLRT 7 × 7, (s) GLRT 9 × 9, and (t) STANR, = 5, = 11, = 0.5.
Figure 9.
Difference images acquired from the Bern data set by using (a) IR, (b) LR, (c) NLMR, (d) MR 3 × 3, (e) MR 5 × 5, (f) MR 7 × 7, (g) MR 9 × 9, (h) NR 3 × 3, (i) NR 5 × 5, (j) NR 7 × 7, (k) NR 9 × 9, (l) INR 3 × 3, (m) INR 5 × 5, (n) INR 7 × 7, (o) INR 9 × 9, (p) GLRT 3 × 3, (q) GLRT 5 × 5, (r) GLRT 7 × 7, (s) GLRT 9 × 9, and (t) STANR, = 5, = 11, = 0.5.
Figure 10.
Change maps acquired from Bern data set by using (a) IR, (b) LR, (c) NLMR, (d) MR 3 × 3, (e) NR 5 × 5, (f) INR 5 × 5, (g) GLRT 3 × 3, and (h) STANR, = 5, = 11, = 0.5.
Figure 10.
Change maps acquired from Bern data set by using (a) IR, (b) LR, (c) NLMR, (d) MR 3 × 3, (e) NR 5 × 5, (f) INR 5 × 5, (g) GLRT 3 × 3, and (h) STANR, = 5, = 11, = 0.5.
Figure 11.
ROC curves of the difference images obtained from the Peixian data set by using (a) MR with different window sizes, STANR; (b) NR with different window sizes, STANR; (c) INR with different window sizes, STANR; (d) GLRT with different window sizes, STANR; and (e) IR, LR, NLMR, MR 7 × 7, NR 7 × 7, INR 7 × 7, GLRT 7 × 7, and STANR, = 5, = 11, = 0.5.
Figure 11.
ROC curves of the difference images obtained from the Peixian data set by using (a) MR with different window sizes, STANR; (b) NR with different window sizes, STANR; (c) INR with different window sizes, STANR; (d) GLRT with different window sizes, STANR; and (e) IR, LR, NLMR, MR 7 × 7, NR 7 × 7, INR 7 × 7, GLRT 7 × 7, and STANR, = 5, = 11, = 0.5.
Figure 12.
ROC curves of the difference images obtained from the Bern data set by using (a) MR with different window sizes, STANR; (b) NR with different window sizes, STANR; (c) INR with different window sizes, STANR; (d) GLRT with different window sizes, STANR; and (e) IR, LR, NLMR, MR 3 × 3, NR 5 × 5, INR 5 × 5, GLRT 3 × 3, and STANR, = 5, = 11, = 0.5.
Figure 12.
ROC curves of the difference images obtained from the Bern data set by using (a) MR with different window sizes, STANR; (b) NR with different window sizes, STANR; (c) INR with different window sizes, STANR; (d) GLRT with different window sizes, STANR; and (e) IR, LR, NLMR, MR 3 × 3, NR 5 × 5, INR 5 × 5, GLRT 3 × 3, and STANR, = 5, = 11, = 0.5.
Table 1.
AUC from using R, LR, NLMR, MR, NR, INR, GLRT, and STANR on the Peixian data set.
Table 1.
AUC from using R, LR, NLMR, MR, NR, INR, GLRT, and STANR on the Peixian data set.
Method | IR | LR | NLMR | MR-7 × 7 | NR-7 × 7 | INR-7 × 7 | GLRT-7 × 7 | STANR |
---|
AUC | 0.908 | 0.906 | 0.995 | 0.992 | 0.981 | 0.994 | 0.994 | 0.997 |
Table 2.
Missed alarms, overall error, detected changes (in number of pixels), Kappa, and F1 score resulting from different approaches on the Peixian data set.
Table 2.
Missed alarms, overall error, detected changes (in number of pixels), Kappa, and F1 score resulting from different approaches on the Peixian data set.
Method | Missed Alarms | Overall Error | Detected Changes | Kappa | F1 Score |
---|
IR | 3635 | 4134 | 2586 | 0.544 | 0.556 |
LR | 2321 | 2871 | 3900 | 0.722 | 0.731 |
NLMR | 1119 | 1360 | 5102 | 0.878 | 0.882 |
MR-7 × 7 | 1134 | 1431 | 5087 | 0.872 | 0.877 |
NR-7 × 7 | 1332 | 1720 | 4889 | 0.845 | 0.850 |
INR-7 × 7 | 1047 | 1302 | 5174 | 0.884 | 0.888 |
GLRT-7 × 7 | 1051 | 1333 | 5170 | 0.882 | 0.886 |
STANR | 855 | 1217 | 5366 | 0.894 | 0.898 |
Table 3.
AUC from using R, LR, NLMR, MR, NR, INR, GLRT, and STANR on the Bern data set.
Table 3.
AUC from using R, LR, NLMR, MR, NR, INR, GLRT, and STANR on the Bern data set.
Method | IR | LR | NLMR | MR-3 × 3 | NR-5 × 5 | INR-5 × 5 | GLRT-3 × 3 | STANR |
---|
AUC | 0.977 | 0.985 | 0.998 | 0.995 | 0.996 | 0.997 | 0.993 | 0.999 |
Table 4.
Missed alarms, overall error, detected changes (in number of pixels), Kappa, and F1 score resulting from different approaches on the Bern data set.
Table 4.
Missed alarms, overall error, detected changes (in number of pixels), Kappa, and F1 score resulting from different approaches on the Bern data set.
Method | Missed Alarms | Overall Error | Detected Changes | Kappa | F1 Score |
---|
IR | 368 | 665 | 787 | 0.699 | 0.703 |
LR | 357 | 546 | 798 | 0.742 | 0.745 |
NLMR | 267 | 395 | 888 | 0.816 | 0.818 |
MR-3 × 3 | 230 | 318 | 925 | 0.851 | 0.853 |
NR-5 × 5 | 234 | 347 | 921 | 0.839 | 0.841 |
INR-5 × 5 | 218 | 303 | 937 | 0.859 | 0.861 |
GLRT-3 × 3 | 222 | 317 | 933 | 0.853 | 0.855 |
STANR | 214 | 302 | 941 | 0.860 | 0.862 |