A Fast and Effective Method for Unsupervised Segmentation Evaluation of Remote Sensing Images
Abstract
:1. Introduction
2. Materials and Methods
2.1. Overview
2.2. Study Area and Data
2.3. Image Segmentation
2.4. Unsupervised Evaluation Using Fast-Global Score
2.5. Accuracy Assessment Measures for the Proposed Method
2.6. Comparison with Other UE Methods and Inter-Segment Heterogeneity Measures
3. Results
3.1. Effectiveness Analysis of DTNP
3.2. Effectiveness Analysis of FGS
3.3. The Performance of FGS on Other Datasets
3.4. Computational Cost
4. Discussion
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Test | Methods | Accuracy Assessment Measures | |||
---|---|---|---|---|---|
QR | OS | US | D | ||
T1 | DTNP | 0.2875 | 0.0849 | 0.2255 | 0.1914 |
MI | 0.5636 | 0.0281 | 0.5512 | 0.3931 | |
BSH | 0.3275 | 0.2282 | 0.1382 | 0.2188 | |
T2 | DTNP | 0.4236 | 0.0338 | 0.3973 | 0.2961 |
MI | 0.4236 | 0.0338 | 0.3973 | 0.2961 | |
BSH | 0.3383 | 0.0708 | 0.2808 | 0.2338 | |
T3 | DTNP | 0.3491 | 0.0589 | 0.3055 | 0.2363 |
MI | 0.3806 | 0.0579 | 0.3517 | 0.2614 | |
BSH | 0.4927 | 0.4528 | 0.1265 | 0.3470 | |
T4 | DTNP | 0.4204 | 0.0533 | 0.3884 | 0.2886 |
MI | 0.4864 | 0.0508 | 0.4575 | 0.3368 | |
BSH | 0.3013 | 0.1906 | 0.1461 | 0.2025 |
Test | Methods | Accuracy Assessment Measures | |||
---|---|---|---|---|---|
QR | OS | US | D | ||
T1 | FGS | 0.2875 | 0.0849 | 0.2255 | 0.1914 |
Johnson’s method | 0.2875 | 0.0849 | 0.2255 | 0.1914 | |
Wang’s method | 0.3016 | 0.0839 | 0.2414 | 0.2012 | |
T2 | FGS | 0.2843 | 0.2293 | 0.0856 | 0.1944 |
Johnson’s method | 0.4242 | 0.3913 | 0.0864 | 0.2974 | |
Wang’s method | 0.2795 | 0.1319 | 0.1702 | 0.1909 | |
T3 | FGS | 0.3281 | 0.1744 | 0.1894 | 0.2212 |
Johnson’s method | 0.3924 | 0.3271 | 0.1285 | 0.2697 | |
Wang’s method | 0.3281 | 0.1744 | 0.1894 | 0.2212 | |
T4 | FGS | 0.3237 | 0.2487 | 0.1184 | 0.2194 |
Johnson’s method | 0.2969 | 0.1171 | 0.2073 | 0.1978 | |
Wang’s method | 0.2915 | 0.0830 | 0.2269 | 0.1929 |
Test | Methods | Accuracy Assessment Measures | |||
---|---|---|---|---|---|
QR | OS | US | D | ||
T5 | FGS | 0.6411 | 0.4502 | 0.3709 | 0.4589 |
Johnson’s method | 0.6503 | 0.5059 | 0.3185 | 0.4650 | |
Wang’s method | 0.6371 | 0.3877 | 0.4307 | 0.4564 | |
T6 | FGS | 0.6231 | 0.3828 | 0.4091 | 0.4437 |
Johnson’s method | 0.6231 | 0.3828 | 0.4091 | 0.4437 | |
Wang’s method | 0.6206 | 0.4276 | 0.3622 | 0.4419 | |
T7 | FGS | 0.6131 | 0.4192 | 0.3392 | 0.4351 |
Johnson’s method | 0.6116 | 0.3260 | 0.4345 | 0.4348 | |
Wang’s method | 0.6276 | 0.4715 | 0.3036 | 0.4467 | |
T8 | FGS | 0.6491 | 0.3881 | 0.4446 | 0.4658 |
Johnson’s method | 0.6439 | 0.4077 | 0.4181 | 0.4615 | |
Wang’s method | 0.6465 | 0.4363 | 0.3924 | 0.4635 |
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Zhao, M.; Meng, Q.; Zhang, L.; Hu, D.; Zhang, Y.; Allam, M. A Fast and Effective Method for Unsupervised Segmentation Evaluation of Remote Sensing Images. Remote Sens. 2020, 12, 3005. https://doi.org/10.3390/rs12183005
Zhao M, Meng Q, Zhang L, Hu D, Zhang Y, Allam M. A Fast and Effective Method for Unsupervised Segmentation Evaluation of Remote Sensing Images. Remote Sensing. 2020; 12(18):3005. https://doi.org/10.3390/rs12183005
Chicago/Turabian StyleZhao, Maofan, Qingyan Meng, Linlin Zhang, Die Hu, Ying Zhang, and Mona Allam. 2020. "A Fast and Effective Method for Unsupervised Segmentation Evaluation of Remote Sensing Images" Remote Sensing 12, no. 18: 3005. https://doi.org/10.3390/rs12183005
APA StyleZhao, M., Meng, Q., Zhang, L., Hu, D., Zhang, Y., & Allam, M. (2020). A Fast and Effective Method for Unsupervised Segmentation Evaluation of Remote Sensing Images. Remote Sensing, 12(18), 3005. https://doi.org/10.3390/rs12183005