Speckle Noise Reduction of Time Series Sar Images Based on Wavelet Transform and Kalman Filter
| Autor: | Yazdan Amerian, Amir Aghabalaei, Hamid Ebadi, Yasser Maghsoudi |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Synthetic aperture radar
Computer science business.industry Speckle reduction Noise reduction ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 0211 other engineering and technologies Wavelet transform Speckle noise 02 engineering and technology Kalman filter Filter (signal processing) 01 natural sciences 010309 optics Reduction (complexity) Speckle pattern 0103 physical sciences Computer vision Artificial intelligence business Image resolution 021101 geological & geomatics engineering |
| Zdroj: | IGARSS |
| DOI: | 10.1109/igarss.2018.8519431 |
| Popis: | Synthetic Aperture Radar (SAR) imaging systems can provide valuable sources of earth observation data for various applications. Speckle noise reduction of images produced by these systems is a challenging issue. In this paper, a novel method is proposed for reducing the speckle noise from time series SAR images. This method is mainly based on wavelet transform and Kalman filter. The proposed method is applied to a time series SAR images acquired by Sentinel-l over Tehran, Iran. To demonstrate the performance of the proposed method, both qualitative and quantitative evaluations are reported compared to those of conventional speckle filtering methods. The experimental results show the good performance and efficiency of the proposed method for the speckle reduction of multitemporal SAR images. As well, the results show that the proposed method can preserve the major edge structures and the spatial resolution while reducing the time of processing. |
| Databáze: | OpenAIRE |
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