Information Content of Very High Resolution SAR Images: Study of Feature Extraction and Imaging Parameters
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Notice bibliographique
Résumé
In this paper, we propose to study the dependence of information extraction technique performance on synthetic aperture radar (SAR) imaging parameters and the selected primitive features (PFs). The evaluation is done on TerraSAR-X data, and the interpretation is realized automatically. In the first part of this paper (use case I), the following issues are analyzed: 1) finding the optimal TerraSAR-X products and their limits of variability and 2) retrieving the number of categories/classes that can be extracted from the TerraSAR-X images using the PFs (gray-level co-occurrence matrix, Gabor filters, quadrature mirror filters, and nonlinear short-time Fourier transform). In the second part of this paper (use case II), we investigate the invariance of the products with the orbit direction and incidence angle. On the one hand, the results show that using ascending looking is better than using descending looking with an average accuracy increase of 7%-8%, approximately. On the other hand, the classification accuracy for the incidence angle varies from a lower value of the incidence to an upper value of the incidence angle (depending on the sensor range) with 4%-5%. The test sites are Venice (Italy), Toulouse (France), Berlin (Germany), and Ottawa (Canada) and are covering as much as possible the huge diversity of modes, types, and geometric resolution configuration of the TerraSAR-X. For the evaluation of all these parameters (resolution, features, orbit looking, and incidence angle), the support-vector-machine classifier is considered. To evaluate the accuracy of the classification, the precision/recall metric is calculated. The first contribution of this paper is the evaluation of different PFs (proposed in the literature for different types of images) and adaptation of these for SAR images. These features are compared (based on the accuracy of the classification) for the first time for a multiresolution pyramid specially built for this purpose. During the evaluation, all the classes were annotated, and a semantic meaning was defined for each class. The second main contribution of this paper is the evaluation of the dependence on the patch size, orbit direction, and incidence angle of the TerraSAR-X. This type of evaluation has not been systematically investigated so far. For the evaluation of the optimal patch, two different patch sizes were defined, with the constrained that the size on ground needs to cover a minimum of one object (e.g., 200 × 200 m on ground). This patch size depends also on the parameters of the data such as resolution and pixel spacing. The investigation of orbit looking and incidence angle is very important for indexing large data sets that has a higher variability of these two parameters. These parameters influence the accuracy of the classification (e.g., if the incidence angle is closer to the lower bounds or closer to the upper bound of the satellite sensor range).
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,002 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle