The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Voi. XXXVII. Part B7. Beijing 2008 
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visual results of weighted RX using simulated image with 
various SNR. This algorithm is selected, because it has more 
sensitivity of noise increase. 
Figure 8. SNR 30:1(a), SNR 20:1(b), SNR 10:1(c), SNR 5:1(d) 
Table (2) and figure (9) show the effect of Signal-to-noise ratio 
on detection performance (AUC). 
Method 
SNR = 5 
SNR = 10 
SNR =20 
SNR = 30 
Global RX 
0.8528 
0.9095 
0.9285 
0.9686 
Local RX_UTD 
0.8568 
0.8806 
0.9189 
0.9801 
Global Weighted 
RX-UTD 
0.6575 
0.7210 
0.8326 
0.9946 
DWEST 
0.6711 
0.8689 
0.9642 
0.9719 
NSWTD 
0.7863 
0.8364 
0.9061 
0.9731 
CFT 
0.7010 
0.8724 
0.9210 
0.9823 
Table 2. AUC in various SNR 
Figure 9. Effect of SNR on AUC 
Also table (3) and figure (10) show the effect of signal-to-noise 
ratio on number of correct detections. 
Method 
SNR = 5 
1 
It 
SNR = 20 
SNR = 30 
Global RX 
38 
44 
49 
53 
Local RXUTD 
37 
38 
41 
64 
Global Weighted 
RX-UTD 
3 
11 
29 
61 
DWEST 
14 
34 
61 
63 
NSWTD 
24 
33 
45 
64 
CFT 
17 
40 
49 
60 
Table 3. Number of correct detections in various SNR 
Effect of Signal To Noise Ratio on Correct Detection 
Figure 10. Effect of SNR on correct detection 
4. CONCLUSION 
Finally our experimental results show that weighted RX-UTD is 
the highest performance algorithm (maximum AUC), NSWTD 
method has maximum number of correct detections, DWEST- 
RX method has minimum number of false alarms, global RX 
algorithm has less sensitivity of various SNR and NSWTD is 
the highest speed method and it is suitable for processing of 
ultraspectral images. 
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