A New Image Fusion Method for Ship Target Enhancement in Spaceborne and Airborne SAR Collaboration
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, we investigate the fusion of spaceborne synthetic aperture radar (SAR) and airborne SAR images and its application to ship target enhancement. In this paper, we propose a new target proposal and clutter copula (TPCC)-based image fusion method for the collaboration of spaceborne and airborne SARs. TPCC enhances the common ship target areas in spaceborne and airborne SAR images via the intersection of target proposals and suppresses the clutter areas by establishing the joint distribution of clutter in the spaceborne and airborne SAR images based on the copula theory. Compared with other commonly used image fusion methods, the target dependence and clutter dependence in the spaceborne and airborne SAR images are newly exploited in TPCC. We demonstrate the superiority of TPCC in terms of target-to-clutter ratios (TCRs) by using composite images combining Gaofen-3 satellite and unmanned aerial vehicle (UAV) SAR images.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it