Double MRF for water classification in SAR images by joint detection and reflectivity estimation
| Autor: | Roger Fjortoft, Loïc Denis, Florence Tupin, Sylvain Lobry |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Synthetic aperture radar
Random field Markov chain Computer science business.industry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 0211 other engineering and technologies Pattern recognition 02 engineering and technology Class (biology) Visualization Statistical classification Artificial intelligence business Constant (mathematics) Image resolution 021101 geological & geomatics engineering |
| Zdroj: | IGARSS HAL |
| DOI: | 10.1109/igarss.2017.8127445 |
| Popis: | Classification of SAR images is a challenging task as the radiometric properties of a class may not be constant throughout the image. The assumption made in most classification algorithms that a class can be modeled by constant parameters is then not valid. In this paper, we propose a classification algorithm based on two Markov random fields that accounts for local and global variations of the parameters inside the image and produces a regularized classification. This algorithm is applied on airborne TropiSAR and simulated SWOT HR data. Both quantitative and visual results are provided, demonstrating the effectiveness of the proposed method. |
| Databáze: | OpenAIRE |
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