An improvement of multiple-component scattering model with rotated covariance matrix for polarimetric SAR decomposition
Bibliographic record
Abstract
It has been validated that the cross-polarized scattering (HV) is caused not only by vegetation but also by rotated dihedrals, then the orientation angle of the rotated dihedrals can be obtained by minimizing the cross-polarized scattering component of covariance matrix. Therefore, this paper presents an improvement of multiple-component scattering model of rotated covariance matrix for Polarimetric SAR decomposition in order to detect the rotated buildings. Based on this model, the oriented buildings can be distinguished from the volume scattering mechanism of forest. Comparisons of the multiple-component decompositions with and without rotation of the covariance matrix are conducted using ESAR L-band Polarimetric SAR data of the Oberpfaffenhofen Test Site Area. Experimental results indicate that the improved decomposition model by implementing a rotation of the covariance matrix can recognize the oriented buildings from volume scattering and achieve a better decomposition result and further more accurate interpretation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".