Super-Resolution Using Dropped-Channel PolSAR Compressive Sensing
| Autor: | Julie Ann Jackson, John Becker |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
020301 aerospace & aeronautics
Computer science business.industry 020208 electrical & electronic engineering ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Data_CODINGANDINFORMATIONTHEORY 02 engineering and technology Superresolution Basis pursuit denoising Compressed sensing 0203 mechanical engineering 0202 electrical engineering electronic engineering information engineering Clutter Computer vision Artificial intelligence business Image resolution Communication channel |
| Zdroj: | 2019 IEEE Radar Conference (RadarConf). |
| Popis: | Previous works introducing dropped-channel polarimetric synthetic aperture radar compressive sensing demonstrated the ability to reconstruct fully-polarimetric imagery from a sub-set of measured channels. In this paper, we showcase the ability of that model to perform super-resolution of images. By leveraging the basis pursuit denoising algorithm and the antenna crosstalk information, we are able to both recover a dropped channel and super-resolve the images in one step. We simulate results using both simple point targets and the GOTCHA dataset. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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