Semi-supervised classification of terrain features in polarimetric SAR images using H/A/α and the general four-component scattering power decompositions
| Autor: | Stephen Michael Dauphin, Katherine M. Simonson, R. Derek West, Robert M. Riley |
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| Rok vydání: | 2014 |
| Předmět: |
Contextual image classification
Pixel business.industry Scattering Computer science ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Terrain Pattern recognition Image (mathematics) Power (physics) Polarimetric sar ComputingMethodologies_PATTERNRECOGNITION Computer vision Artificial intelligence business Feature detection (computer vision) |
| Zdroj: | ACSSC |
| Popis: | In an effort to enhance image classification of terrain features in fully polarimetric SAR images, this paper explores the utility of combining the results of two state-of-the-art decompositions along with a semi-supervised classification algorithm to classify each pixel in an image. Each pixel is labeled either with a pre-determined classification label, or labeled as unknown. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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