一种图像回归与关联关系特征融合的遥感影像变化检测方法
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马宗方,郝凡,宋琳,麻瑞
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Image Regression and Association-based Feature Fusion for Remote Sensing Image Change Detection
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Zongfang MA,Fan HAO,Lin SONG,Rui MA
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表4 不同方法在Texas数据集的变化检测精度
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Table 4 Change detection accuracy of different methods on Texas dataset
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方法 | FN | FP | OE | Ra | Rp | Rm | Rf | Ka |
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PCC | 32 610 | 74 573 | 107 183 | 0.913 5 | 0.571 | 0.247 3 | 0.429 | 0.601 1 | CVA | 30 074 | 149 178 | 179 252 | 0.855 4 | 0.405 6 | 0.228 1 | 0.594 4 | 0.455 9 | IR-MAD | 83 184 | 56 027 | 139 211 | 0.887 7 | 0.464 9 | 0.630 8 | 0.535 1 | 0.350 4 | SCCN | 8 339 | 180 476 | 188 815 | 0.847 7 | 0.406 3 | 0.063 2 | 0.593 7 | 0.491 3 | FPMSMCD | 21 502 | 51 862 | 73 364 | 0.940 8 | 0.680 3 | 0.163 1 | 0.319 7 | 0.717 4 | SCASC | 86 705 | 9 941 | 96 646 | 0.922 | 0.819 6 | 0.657 5 | 0.180 4 | 0.448 5 | GIR-MRF | 1 935 | 23 814 | 25 749 | 0.979 2 | 0.845 1 | 0.014 7 | 0.154 9 | 0.898 2 | IRAF | 4 322 | 5 588 | 9 910 | 0.992 | 0.958 | 0.032 8 | 0.042 | 0.958 1 |
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