POLARIMETRIC SAR TOMOGRAPHY USING &lt;I&gt;l&lt;/I&gt;&lt;sub&gt;2,1&lt;/sub&gt; MIXED NORM SPARSE RECONSTRUCTION METHOD

Xing, Shu; Dai, Dahai; Li, Yongzhen; Wang, Xuesong

doi:10.2528/pier12051408

Cited by 12 publications

(11 citation statements)

References 41 publications

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“…On the one hand, it is expected that the use of an L-band polarimetric sensor will greatly improve the inversion results because of both the higher contrast between ground and vegetation and the lower impact of soil roughness [13]. On the other hand, the model-based decomposition strategies applied to PolInSAR observables could potentially lead to a better retrieval performance through the separation of coherency/covariance interferometric matrices expressed in terms of ground and canopy parameters [47][48][49]. …”

Section: Discussionmentioning

confidence: 99%

Polarimetric Sar Model for Soil Moisture Estimation Over Vineyards at C-Band

Ballester-Berman¹,

Vicente-Guijalba²,

López-Sánchez³

2013

PIER

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Abstract-In this paper we propose a two-component polarimetric model for soil moisture estimation on vineyards suited for C-band radar data. According to a polarimetric analysis carried out here, this scenario is made up of one dominant direct return from the soil and a multiple scattering component accounting for disturbing and nonmodeled signal fluctuations from soil and short vegetation. We propose a combined X-Bragg/Fresnel approach to characterize the polarized direct response from soil. A validation of this polarimetric model has been performed in terms of its consistency with respect to the available data both from RADARSAT-2 and from indoor measurements. High inversion rates are reported for different phenological stages of vines, and the model gives a consistent interpretation of the data as long as the volume component power remains about or below 50% of the surface contribution power. However, the scarcity of soil moisture measurements in this study prevents the validation of the algorithm in terms of the accuracy of soil moisture retrieval and an extensive campaign is required to fully demonstrate the validity of the model. Different sources of mismatches between the model and the data have been also discussed and analyzed.

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Section: Discussionmentioning

confidence: 99%

Polarimetric Sar Model for Soil Moisture Estimation Over Vineyards at C-Band

Ballester-Berman¹,

Vicente-Guijalba²,

López-Sánchez³

2013

PIER

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“…Recently, CS theory has been used in SAR signal processing and image formation [21][22][23][24]. In this paper, we exploit CS theory for despeckling of SAR image.…”

Section: Introductionmentioning

confidence: 99%

Sar Image Despeckling by Selective 3d Filtering of Multiple Compressive Reconstructed Images

Iqbal¹,

Chen²,

Yang³

et al. 2013

PIER

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Abstract-A despeckling technique based on multiple image reconstruction and selective 3-dimensional filtering is proposed. Multiple SAR images are reconstructed from a single SAR image by employing compressive sensing (CS) theory. In order to obtain multiple images from single SAR image, multiple subsets of pixels are selected from input SAR image by imposing restriction that each subset has at least 20% different pixels from any other subset. These subsets are taken as measurement vectors in CS framework to obtain multiple SAR images. A despeckled image is obtained by employing selective 3-dimensional filtering to multiple reconstructed SAR image. The proposed technique is tested on single look complex TerraSAT-X data set, and experimental results exhibit that the proposed technique outperformed benchmark despekling methods in terms of visual quality and despeckling quality metrics.

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“…Similar approaches have been reported in microwave and ultrasonic imaging [24,25]. Several other inverse and imaging problems can potentially benefit from limited region tomography method proposed in this paper, including but not limited to [27][28][29][30][31][32][33][34][35]. In [25], a pre-processing method was used to apply a bandpass filtering to multiple-frequency data for microwave tomography.…”

Section: Image Reconstructionmentioning

confidence: 99%

High Definition Electrical Capacitance Tomography for Pipeline Inspection

Evangelidis¹,

Ma²,

Soleimani³

2013

PIER

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Abstract-Pipelines made of dielectric materials such as Polyethylene (PE) are becoming increasingly popular. With no suitable inspection technique for dielectric pipes, there is an urgent need to develop new technology for their inspection. This paper presents a novel pipe inspection technique using Electrical Capacitance Tomography (ECT) imaging. Traditionally ECT is used for industrial process tomography as a low resolution but fast tomographic imaging technique. Typically commercial ECT can provide a resolution of approximately 10 percent of the imaging region. In this paper a limited region tomography technique is developed take into account prior knowledge about the geometry of the pipe. This has significantly enhanced the imaging resolution of the ECT system, making it a viable pipe inspection solution. The experimental results in this study demonstrate an interior wall loss area as small as 0.195 percent of the ECT cross sectional imaging region is repeatable and can be reliably detected. A narrowband pass filter method (NPFM) is used as a means to limit the region for the ECT algorithm. This results in an unprecedented resolution, making ECT a viable non-destructive evaluation (NDE) technique for plastic pipes. The NDE application of the ECT for PE pipes is demonstrated in this paper with several experimental results. A wall loss of depth of 1.5 mm could be detected for an ECT sensor array of 150 mm in diameter, showing a high resolution and high definition ECT (HD-ECT) imaging that has not been reported before.

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POLARIMETRIC SAR TOMOGRAPHY USING <I>l</I><sub>2,1</sub> MIXED NORM SPARSE RECONSTRUCTION METHOD

Cited by 12 publications

References 41 publications

Polarimetric Sar Model for Soil Moisture Estimation Over Vineyards at C-Band

Polarimetric Sar Model for Soil Moisture Estimation Over Vineyards at C-Band

Sar Image Despeckling by Selective 3d Filtering of Multiple Compressive Reconstructed Images

High Definition Electrical Capacitance Tomography for Pipeline Inspection

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