SAR Flow Ice Separation Algorithm Combined with Saliency Detection

Fig. 4. Saliency maps obtained by different algorithms. (a) Original image; (b) GT; (c) DRFI; (d) RBD; (e) MR; (f) GS; (g) BSCA; (h) MAP; (i) SRD; (j) proposed algorithm

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Fig. 5. Comparison of P-R curves of different algorithms

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Fig. 6. Comparison of MAE values of different algorithms

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Fig. 7. MAE in different datasets

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Fig. 8. F_measure in different datasets

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Fig. 9. Comparison of segmentation methods. (a) Original image; (b) GT; (c) proposed algorithm; (d) MACWE; (e) MRF; (f) MRF_BCD

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Fig. 10. MIoU of each segmentation method

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Table 1. Information table of seascape images
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Table 1. Information table of seascape images
Parameter Content
Center coordinate (13°41'49.5″W, 80°53'27.6″N)
Greenwich mean time 2015-09-03T16∶48∶28
Resolution 12.5 m
Angle of incidence 27.06°
Image size 2690×6002

Table 2. Running time of different algorithms
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Table 2. Running time of different algorithms
Algorithm RBD MR GS DRFI BSCA MAP SRD Proposedalgorithm DRFI⁺ Proposedalgorithm⁺
Time /s 0.302 0.307 0.323 2.821 1.236 0.539 0.918 2.832 1.051 1.063

Table 3. Comparison of F_measure values of different algorithms

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Table 3. Comparison of F_measure values of different algorithms

Dataset	BSCA	MAP	SRD	DRFI	RBD	GS	MR	Proposed algorithm
a	0.798	0.797	0.807	0.781	0.788	0.619	0.780	0.819
b	0.573	0.478	0.378	0.696	0.227	0.354	0.570	0.784
c	0.703	0.653	0.633	0.758	0.722	0.586	0.671	0.763
d	0.478	0.406	0.373	0.742	0.331	0.282	0.332	0.764

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Hongxia Yang, Hao Guo, Yan Gao, Jubai An. SAR Flow Ice Separation Algorithm Combined with Saliency Detection[J]. Laser & Optoelectronics Progress, 2020, 57(20): 201010

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