Remote Sensing Technology and Application, Volume. 39, Issue 2, 405(2024)
Improved Markov Random Field for Building Segmentation in SAR Images
Figures & Tables(12)
Fig. 3. Segmentation results of different feature fusion algorithms
Table 1. Comparison of the segmentation performance of different algorithms for Scene 1
View tableView in ArticleTable 1. Comparison of the segmentation performance of different algorithms for Scene 1
算法 DR FAR CCR Dice 传统MRF 55.46 8.10 88.27 69.17 文献[ 13 ]92.96 12.08 95.30 90.30 本文算法 89.39 5.51 96.25 91.87
Table 2. Comparison of the segmentation performance of different algorithms for Scene 2
View tableView in ArticleTable 2. Comparison of the segmentation performance of different algorithms for Scene 2
算法 DR FAR CCR Dice 传统MRF 87.29 40.04 94.21 71.09 文献[ 13 ]98.27 43.74 93.63 71.55 本文算法 97.34 37.54 95.01 76.09
Table 3. Comparison of the segmentation performance of different algorithms for Scene 3
View tableView in ArticleTable 3. Comparison of the segmentation performance of different algorithms for Scene 3
算法 DR FAR CCR Dice 传统MRF 71.89 45.97 93.78 61.69 文献[ 13 ]95.48 52.26 92.41 63.65 本文算法 80.67 33.36 95.84 72.99
Table 4. Comparison of the segmentation performance of different algorithms for Scene 4
View tableView in ArticleTable 4. Comparison of the segmentation performance of different algorithms for Scene 4
算法 DR FAR CCR Dice 传统MRF 75.88 16.17 92.35 79.66 文献[ 13 ]99.87 43.48 84.81 72.19 本文算法 89.90 16.96 94.38 86.33
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Jia ZHAO, Daoxiang AN. Improved Markov Random Field for Building Segmentation in SAR Images[J]. Remote Sensing Technology and Application, 2024, 39(2): 405
Paper Information
Category: Research Articles
Received: Nov. 23, 2022
Accepted: --
Published Online: Aug. 13, 2024
The Author Email: ZHAO Jia (1541735534@qq.com)
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