Multi-Scale Proposal Generation for Ship Detection in SAR Images
Abstract
:1. Introduction
- A ship generally has a different scattering characteristics from its surroundings;
- A ship generally has some components with strong scattering;
- There are edges between a ship and its surroundings;
- A ship generally has a closed contour.
- The generator obtains components of ships by superpixel algorithm, and explores ships by hierarchical grouping;
- The generator obtains proposals from the superpixels that contain at least one strong scattering component;
- The generator measures a proposal by the difference of the edge density between the inside and near the borders of the proposal;
- The generator measures a proposal by the completeness and the tightness of the contour.
2. Ship Proposal Generator
2.1. Framework
Algorithm 1: Hierarchical Grouping using Superpixels and Strong Scattering Components. |
2.2. Edges and Superpixels
2.3. Hierarchical Grouping
2.4. Proposal Scoring
2.4.1. Edge Scoring
2.4.2. Contour Scoring
3. Results
3.1. Evaluation of Four Procedures
3.1.1. Evaluation of Hierarchical Superpixels Grouping
Variation of Initial Superpixels Size
Hierarchical Superpixels Grouping versus Multi-scale Superpixels Segmentation
Hierarchical Superpixels Grouping versus Sliding Windows
3.1.2. Evaluation of Strong Scattering Components Information
3.1.3. Evaluation of Edges Scoring and Contours Scoring
3.1.4. Evaluation of Multi-Scale Ship Proposal Generation
3.2. Comparison with the State-of-the-Art Methods
4. Discussion
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Methods | AUC | ABO Score | Average Proposals | |
---|---|---|---|---|
Multi-scale Superpixels Segmentation | 0.53 | 0.68632 | 2031 | |
0.54 | 0.69810 | 12,603 | ||
0.51 | 0.64609 | 862 | ||
0.49 | 0.62862 | 1208 | ||
Multi-scale Sliding Windows | 0.21 | 0.50069 | 5891 | |
0.22 | 0.51710 | 2295 | ||
0.18 | 0.45826 | 3882 | ||
0.14 | 0.44292 | 1208 | ||
Without Strong Scattering Components Information | 0.53 | 0.64150 | 1146 | |
0.55 | 0.69891 | 2288 | ||
Without Edges Scoring | 0.54 | 0.63142 | 260 | |
0.57 | 0.69363 | 869 | ||
Without Contours Scoring | 0.46 | 0.63121 | 261 | |
0.46 | 0.70291 | 869 | ||
Proposed method | 0.55 | 0.62785 | 261 | |
0.58 | 0.70334 | 868 |
Methods | k | Large Ships | Middle Ships | Small Ships | ||||||
---|---|---|---|---|---|---|---|---|---|---|
ABO | AUC | Best Recall | ABO | AUC | Best Recall | ABO | AUC | Best Recall | ||
Multi Scale Sliding Windows | 0.32 | 0.01 | 0.07 | 0.53 | 0.22 | 0.61 | 0.55 | 0.24 | 0.61 | |
0.53 | 0.28 | 0.62 | 0.53 | 0.28 | 0.62 | 0.49 | 0.20 | 0.40 | ||
Multi-scale Superpixels Segmentation | 0.54 | 0.20 | 0.50 | 0.73 | 0.51 | 0.92 | 0.71 | 0.60 | 0.92 | |
0.69 | 0.33 | 0.82 | 0.72 | 0.54 | 0.91 | 0.67 | 0.58 | 0.86 | ||
Proposed Method | 15 | 0.57 | 0.32 | 0.60 | 0.65 | 0.59 | 0.81 | 0.63 | 0.58 | 0.75 |
0.69 | 0.37 | 0.84 | 0.73 | 0.61 | 0.93 | 0.68 | 0.61 | 0.84 |
Methods | Large Ships | Middle Ships | Small Ships | All Ships | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
ABO | AUC | Best Recall | ABO | AUC | Best Recall | ABO | AUC | Best Recall | ABO | AUC | Best Recall | |
Saliency Filtering [29] | 0.44 | 0.39 | 0.40 | 0.56 | 0.62 | 0.64 | 0.46 | 0.40 | 0.44 | 0.51 | 0.46 | 0.49 |
LCVIWE [1] | 0.44 | 0.44 | 0.44 | 0.43 | 0.44 | 0.44 | 0.14 | 0.05 | 0.05 | 0.33 | 0.18 | 0.18 |
ITBTD [3] | 0.41 | 0.29 | 0.32 | 0.36 | 0.13 | 0.16 | 0.25 | 0.06 | 0.08 | 0.32 | 0.09 | 0.12 |
Objectness Learning [54] | 0.53 | 0.07 | 0.37 | 0.53 | 0.14 | 0.45 | 0.54 | 0.21 | 0.52 | 0.52 | 0.18 | 0.49 |
Proposed Method | 0.75 | 0.41 | 0.94 | 0.74 | 0.64 | 0.94 | 0.67 | 0.59 | 0.81 | 0.70 | 0.59 | 0.85 |
Methods | Saliency Filtering | LCVIWE | ITBTD | Objectness Learning | Proposed Method |
---|---|---|---|---|---|
Time | 0.43492s | 0.01195s | 1.62894s | 15.99199s | 1.34954s |
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Liu, N.; Cao, Z.; Cui, Z.; Pi, Y.; Dang, S. Multi-Scale Proposal Generation for Ship Detection in SAR Images. Remote Sens. 2019, 11, 526. https://doi.org/10.3390/rs11050526
Liu N, Cao Z, Cui Z, Pi Y, Dang S. Multi-Scale Proposal Generation for Ship Detection in SAR Images. Remote Sensing. 2019; 11(5):526. https://doi.org/10.3390/rs11050526
Chicago/Turabian StyleLiu, Nengyuan, Zongjie Cao, Zongyong Cui, Yiming Pi, and Sihang Dang. 2019. "Multi-Scale Proposal Generation for Ship Detection in SAR Images" Remote Sensing 11, no. 5: 526. https://doi.org/10.3390/rs11050526