## 3 Results
### Detection Performance
The false color image, ground-truth maps, the result of over segmentation, the label map \(P\) obtained from the selective search, and the corresponding color detection graphs for the ABU Airport image are shown in Figure 6. The threshold \(T\) in the region fusion is set at 1.95 for the ABU Airport image because of the optimal regional fusion effect. The sizes of the dual-window for the ABU Airport image are set at (11,15) for CRD, CRBORAD, and SSCRD, which is a typical sample of unbefitting dual-window sizes for CRD in the ABU Airport image. As can be seen from the CRD detection results (Figure 6e), except that the position of the left aircraft is vaguely detected, the rest of the anomalies are not detected. The shapes and outlines of the aircraft are blurred. By comparing the detection result of CRBORAD (Figure 6f) with the ground-truth map (Figure 6b), the position of the aircraft on the left side is detectable and its shape is roughly distinguished. The positions of the two smaller aircraft on the right side are indistinct. The shape and outer profile are totally unidentifiable. In the detection results of SSCRD (Figure 6h), the position and shape of the aircraft on the left side can be clearly detected, and the position of the two aircraft on the right side are clearly detected, but their shapes and contours cannot be successfully detected. Moreover, the misjudgement of the detection graph is similar to that of CRD. There is some misjudgement at the bottom left of the image, in which some background pixels are judged to be abnormal, which may be attributed to the basic principle of CRD. The extremely high scores of those with misjudged backgrounds are responsible for the ambiguity of anomaly detection. Compared with CRD, CRBORAD, and SSCRD, the score of the larger aircraft on the left obtained from LRSRD is sufficiently high to make this anomaly clearly visible. However, the two smaller aircraft on the right side are still indistinct. LRSRD has a significantly higher false alarm rate. Many background pixels are displayed in the anomaly detection image. Figure 4: Cont. Figure 4: Color detection maps for San Diego-II image with dual-window sizes (9,13). (**a**) False color image; (**b**) ground-truth map; (**c**) over-segmentation; (**d**) label map P; (**e**) the detection result of CRD; (**f**) the detection result of CRBORAD; (**g**) the detection result of LRSRD; (**h**) the detection result of SSCRD. Figure 5: ROC curves for San Diego-II dataset with dual-window sizes (9,13) for CRD, CRBORAD, and SSCRD. Figure 6: \(Cont\). of the CRD is 80.88. Compared with CRD, the ROC curve of CRBORAD is significantly closer to the upper left corner of the coordinate axis. When the false alarm rate is 0.1, the probability of detection reaches 0.8. The AUC value (in percent) of CRBORAD is 93.78. Compared with CRBORAD, the ROC curve of SSCRD is closer to the upper left corner of the coordinate axis, and the probability of detection reaches 0.9 when the false alarm rate is 0.1. The ROC curve of SSCRD is much closer to the upper left corner of the coordinate axis than that of CRD and CRBORAD, and the corresponding AUC value of SSCRD is 96.74, showing a considerable improvement to CRD and superior detection performance. Due to the failure detection of two small aircraft, the ROC curve (in percent) of LRSRD is slightly lower than CRBORAD and SSCRD, and the AUC value (in percent) of LRSRD is 92.99.