Stereo-mate generation of high-resolution satellite imagery using a parallel projection model
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Synthesis methods to create a stereo-mate of satellite imagery from an orthophoto have been developed in many previous studies. If these methods are applied in an urban area where there are many adjacent tall buildings, stereo viewing is inhibited by occlusion in the orthophoto and its stereo-mate. In high-resolution satellite imagery, the in-track view angle of the image is usually far from vertical; consequently, the occluded area near tall structures occupies a large area, and this severely affects stereo viewing. This study proposes a different approach to creating stereo-mates for high-resolution satellite imagery by projection of the digital surface model (DSM) draped by the original single image onto a fictitious satellite sensor model. The main benefit of this method is enhanced stereo viewing by arranging the fictitious sensor model to reduce occlusion area. The physical sensor model of the original image is previously derived by parallel projection model, and then the stereo-mate fictitious sensor model is determined from the physical sensor model.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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