Speckle filtering of synthetic aperture radar images: A review

Lee, J. S.; Jurkevich, L.; Dewaele, Piet; Wambacq, Patrick; Oosterlinck, André

doi:10.1080/02757259409532206

Cited by 532 publications

(278 citation statements)

References 33 publications

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“…A multi-temporal approach was applied to the stack of co-registered SAR intensity images (Table 1) [32]. Granular salt and pepper patterns, referred to as "speckle" in SAR images, occurs when coherent processing of the backscatter returns from consecutive radar pulses [75,76]. We selected a moving weighted function with a filter window size of 5 × 5 pixels to reduce speckle.…”

Section: Sar Data Acquisition and Processingmentioning

confidence: 99%

A Collection of SAR Methodologies for Monitoring Wetlands

et al. 2015

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Abstract:Wetlands are an important natural resource that requires monitoring. A key step in environmental monitoring is to map the locations and characteristics of the resource to better enable assessment of change over time. Synthetic Aperture Radar (SAR) systems are helpful in this way for wetland resources because their data can be used to map and monitor changes in surface water extent, saturated soils, flooded vegetation, and changes in wetland vegetation cover. We review a few techniques to demonstrate SAR capabilities for wetland monitoring, including the commonly used method of grey-level thresholding for mapping surface water and highlighting changes in extent, and approaches for polarimetric decompositions to map flooded vegetation and changes from one class of land cover to another. We use the Curvelet-based change detection and the Wishart-Chernoff Distance approaches to show how they substantially improve mapping of flooded vegetation and flagging areas of change, respectively. We recommend that the increasing availability SAR data and the proven ability of these data to map various components of wetlands mean SAR should be considered as a critical component of a wetland monitoring system.

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Section: Sar Data Acquisition and Processingmentioning

confidence: 99%

A Collection of SAR Methodologies for Monitoring Wetlands

et al. 2015

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“…The natural environment, characterized by distributed targets, is mainly affected by the speckle effect. To reduce this effect, polarimetric speckle filtering using the refined Lee filter is applied [52,53]. This filter aims to preserve the structure of the image, i.e., the edges, while filtering homogenous areas.…”

Section: Polarimetric Speckle Filteringmentioning

confidence: 99%

Landslide Mapping in Vegetated Areas Using Change Detection Based on Optical and Polarimetric SAR Data

2016

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Abstract:Mapping of landslides, quickly providing information about the extent of the affected area and type and grade of damage, is crucial to enable fast crisis response, i.e., to support rescue and humanitarian operations. Most synthetic aperture radar (SAR) data-based landslide detection approaches reported in the literature use change detection techniques, requiring very high resolution (VHR) SAR imagery acquired shortly before the landslide event, which is commonly not available. Modern VHR SAR missions, e.g., Radarsat-2, TerraSAR-X, or COSMO-SkyMed, do not systematically cover the entire world, due to limitations in onboard disk space and downlink transmission rates. Here, we present a fast and transferable procedure for mapping of landslides, based on change detection between pre-event optical imagery and the polarimetric entropy derived from post-event VHR polarimetric SAR data. Pre-event information is derived from high resolution optical imagery of Landsat-8 or Sentinel-2, which are freely available and systematically acquired over the entire Earth's landmass. The landslide mapping is refined by slope information from a digital elevation model generated from bi-static TanDEM-X imagery. The methodology was successfully applied to two landslide events of different characteristics: A rotational slide near Charleston, West Virginia, USA and a mining waste earthflow near Bolshaya Talda, Russia.

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“…One is de-noised methods based on spatial filtering, and the other is de-noised methods based on multi-scale transform. For example, Lee filter (Lee et al, 1994), total variation regularization de-noising methods (Eom, 2011) and non-local means (NLM) de-noising methods (Torres, 2013) are de-noised methods base on spatial filtering; Bayesian wavelet shrinkage with edge detection for SAR image despeckling (Dai et al, 2004), and the SAR image despeckling based on nonsubsampled shearlet transform (Hou et al, 2012) are de-noised methods based on transform domain. In recent years, with the continuous improvement of the theory of multi-scale and multi-resolution transform, the de-noised methods based on transform domain are widely used in SAR image de-noising.…”

Section: Introductionmentioning

confidence: 99%

SAR Image De-Noising based on GNL-Means with Optimized Pixel-Wise Weighting in Non-Subsample Shearlet Domain

Liu

Liu²,

Zhao³

2016

CIS

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SAR images have been widely used in many fields such as military and remote sensing. So the suppression of the speckle has been an important research issues. To improve the visual effect of non-local means, generalized non-local (GNL) means with optimized pixel-wise weighting is applied to shrink the coefficients of non-subsample Shearlet transform (NSST) of SAR image. The new method can optimize the weight of GNL, which not only improve the PSNR of de-noised image, but also can significantly enhance the visual effect of de-noising image.

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Speckle filtering of synthetic aperture radar images: A review

Cited by 532 publications

References 33 publications

A Collection of SAR Methodologies for Monitoring Wetlands

A Collection of SAR Methodologies for Monitoring Wetlands

Landslide Mapping in Vegetated Areas Using Change Detection Based on Optical and Polarimetric SAR Data

SAR Image De-Noising based on GNL-Means with Optimized Pixel-Wise Weighting in Non-Subsample Shearlet Domain

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